Qureos Mentor

Qualcomm

Qualcomm is a leading company in semiconductor manufacturing, specializing in wireless technology and mobile computing. With a focus on delivering intelligent computing solutions, Qualcomm is involved in various sectors including automotive, Internet of Things, and 5G technology. The company is headquartered in San Diego, CA, and has a significant global presence with over 10,000 employees. Qualcomm is publicly traded and continues to innovate in areas such as augmented reality and networking.

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Technologies, Inc.
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Engineering Group, Engineering Group &gt; Software Engineering
<p></p><p><b>General Summary:
</b></p><p>As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.
</p><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
</li></ul><p></p><p><b>Preferred Qualifications:
</b></p><ul><li>1+ year of experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul><ul><li>1+ year of experience with Database Management Software.
</li></ul><ul><li>1+ year of experience with API.
</li></ul><p>&bull; 1+ year of work experience with Git, Perforce, or Source Code Management System.
</p><p></p><p><b>Principal Duties and Responsibilities:
</b></p><p>&bull; Applies Software knowledge to assist and support the design, development, creation, modification, and validation of embedded and cloud edge software, applications, and/or specialized utility programs.
</p><p>&bull; Analyzes user needs and software requirements.
</p><p>&bull; Designs and implements small software features for products and systems.
</p><p>&bull; Participates in the design, coding for small features, unit testing, minor debugging fixes, and integration efforts to ensure projects are completed on schedule.
</p><p>&bull; Assists in performing code reviews and regression tests as well as the triaging of issues to ensure the quality of code.
</p><p>&bull; Collaborates with others inside project team to accomplish project objectives.
</p><p>&bull; Writes technical documentation for Software projects.
</p><p></p><p><b>Level of Responsibility:
</b></p><ul><li>Works under supervision.
</li></ul><ul><li>Decision-making affects direct area of work and/or work group.
</li></ul><ul><li>Requires verbal and written communication skills to convey basic, routine factual information.
</li></ul><ul><li>Tasks require multiple steps which can be performed in various orders; some planning, problem-solving, and prioritization must occur to complete the tasks effectively.
</li></ul><p></p><div><p>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</p></div><p></p><p><b>To all Staffing and Recruiting Agencies </b>: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
</p><p><b>EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
</b></p><p></p><p>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.<br>
</p><p></p><p><b>Pay range </b><b>and Other Compensation &amp; Benefits </b><b>:
</b></p>$94,200.00 - $141,200.00
<p></p><p>The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer &ndash; and you can review more details about our US benefits at this link .
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

#Automotive Software Test Engineer

<div>
 <strong>
  Company
  <br/>
  <br/>
 </strong>
 Qualcomm Technologies, Inc.
 <br/>
 <br/>
 <strong>
  Job Area
  <br/>
  <br/>
 </strong>
 Engineering Group, Engineering Group &gt; Software Engineering
 <br/>
 <br/>
 <strong>
  General Summary
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   This position is not eligible for Qualcomm immigration sponsorship.***
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 As a Qualcomm Product Software Engineer , this role requires working on Product Software development and testing tasks for various programs (e.g. Smartphones ( Linux, Android OS etc.), Computing devices (e.g. Laptops, Servers) , Automotive Infotainment &amp; ADAS systems ,and other consumer &amp; Industrial IoT products). You will work and collaborate with various other Qualcomm Engineering teams e.g. Software, Systems , Hardware, Architecture and Test teams for delivering end to end product software solution for such programs.
 <br/>
 <br/>
 <strong>
  Software Integration Tasks
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Integrate software components and configurations to meet product specifications.
  </li>
  <li>
   Maintain and enhance automation for continuous integration systems.
  </li>
  <li>
   Resolve build failures, resolve any software interface dependencies.
  </li>
  <li>
   Create and maintain build scripts to optimize the build generation process.
  </li>
  <li>
   Manage software configuration using version control system ( e.g. Perforce or GIT or Github etc.)
  </li>
  <li>
   Announce and release new software baselines.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Product Software Sanity Testing
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Sanity test the incremental builds to catch any regression issues due to new integration tasks. This testing happens on-target devices, simulators and reference platforms.
  </li>
  <li>
   Debug any sanity test failures. This requires understanding of common on-target debugging tools such as JTAG, ADB , simulators, log analysis etc.
  </li>
  <li>
   Create scripts to automate the test scenarios and process logs.
  </li>
  <ul>
   <li>
    Create test plans to cover test coverage for new features being enabled through software integration cycles.
   </li>
   <li>
    Collaborate for design and code-reviews with other technical &amp; business team members.
    <br/>
    <br/>
    <br/>
   </li>
  </ul>
 </ul>
 <strong>
  Minimum Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 OR
 <br/>
 <br/>
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
 <br/>
 <br/>
 OR
 <br/>
 <br/>
 PhD in Engineering, Information Systems, Computer Science, or related field.
 <br/>
 <br/>
 <ul>
  <li>
   2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Understanding of OPEN BMC and Operating Systems (CentOs/UBantu/RHEL) for x86, ARM64, and RISC-V 64-bit server platforms.
  </li>
  <li>
   Experience with open-source benchmarking tools (DCPerf, Kubernetes, VectorDBBench) and AIML module such as PyTorch and vLLM, etc.
  </li>
  <li>
   Knowledge of different debugging tool such as TRACE32,OpenOCD,etc for compute and IoT projects.
  </li>
  <li>
   Experience with Software development, debugging and testing with ARM or x86 based compute and Server product development for Linux based OS.
  </li>
  <li>
   Experience with using open source software, enablement of such software for different hardware platforms by collaborating with software &amp; hardware teams.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Principal Duties And Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Applies Software knowledge to assist and support the design, development, creation, modification, and validation of embedded and cloud edge software, applications, and/or specialized utility programs.
  </li>
  <li>
   Analyzes user needs and software requirements.
  </li>
  <li>
   Designs and implements small software features for products and systems.
  </li>
  <li>
   Participates in the design, coding for small features, unit testing, minor debugging fixes, and integration efforts to ensure projects are completed on schedule.
  </li>
  <li>
   Assists in performing code reviews and regression tests as well as the triaging of issues to ensure the quality of code.
  </li>
  <li>
   Collaborates with others inside project team to accomplish project objectives.
  </li>
  <li>
   Writes technical documentation for Software projects.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Level Of Responsibility
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Works under supervision.
  </li>
  <li>
   Decision-making affects direct area of work and/or work group.
  </li>
  <li>
   Requires verbal and written communication skills to convey basic, routine factual information.
  </li>
  <li>
   Tasks require multiple steps which can be performed in various orders; some planning, problem-solving, and prioritization must occur to complete the tasks effectively.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
 <br/>
 <br/>
 <strong>
  To all Staffing and Recruiting Agencies
 </strong>
 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
 <br/>
 <br/>
 <strong>
  EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
  <br/>
  <br/>
 </strong>
 Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
 <br/>
 <br/>
 <strong>
  Pay Range And Other Compensation &amp; Benefits
  <br/>
  <br/>
 </strong>
 $111,300.00 - $166,900.00
 <br/>
 <br/>
 The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer &ndash; and you can review more details about our US benefits at this link.
 <br/>
 <br/>
 If you would like more information about this role, please contact Qualcomm Careers.
</div>


#Product Software Engineer

<div>
 <strong>
  <strong>
   Company:
   <br/>
   <br/>
  </strong>
 </strong>
 Qualcomm Middle East Information Technology Company LLC
 <br/>
 <br/>
 <strong>
  <strong>
   Job Area:
   <br/>
   <br/>
  </strong>
 </strong>
 Engineering Group, Engineering Group &gt; Software Engineering
 <br/>
 <br/>
 <strong>
  <strong>
   General Summary:
   <br/>
   <br/>
  </strong>
 </strong>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You&rsquo;ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.
 <br/>
 <br/>
 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region.
 <br/>
 <br/>
 As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
 <br/>
 <br/>
 <strong>
  <strong>
   About The Role
   <br/>
   <br/>
  </strong>
 </strong>
 We are seeking a Full-Stack Machine Learning Engineer to join our team, bridging AI solutions development with AI platform engineering for Qualcomm&rsquo;s AI Inference Suite and rack-scale data center deployments. This role involves designing, delivering, and supporting end-to-end AI services, agentic workflows, and fine-tuning pipelines, while enabling lifecycle automation, orchestration, and observability for large-scale data center environments.
 <br/>
 <br/>
 You will bring a strong combination of full-stack engineering expertise, machine learning proficiency, and infrastructure knowledge to build robust, scalable AI systems.
 <br/>
 <br/>
 <strong>
  <strong>
   Key Responsibilities Will Include:
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   API Development &amp; Optimization: Build and optimize API serving layers for AI inference workloads, ensuring model and hardware efficiency.
  </li>
  <li>
   Agentic Workflows &amp; RAG Pipelines: Develop intelligent agents and retrieval-augmented generation workflows using frameworks such as LangChain and crew.ai.
  </li>
  <li>
   Model Lifecycle Management: Implement production-grade bring-your-own-model and fine-tuning flows, including dataset ingestion, orchestration, evaluation, and deployment.
  </li>
  <li>
   LLM Runtime Integration: Work with various LLM runtimes (e.g., vLLM, Dynamo, llm-d) and leverage inference optimization techniques.
  </li>
  <li>
   SDK &amp; Tooling Contributions: Contribute to AI Inference Suite SDKs (Python/TypeScript/Java/Rust), CLI tools, and reference applications.
  </li>
  <li>
   Cluster Management: Design and maintain AI cluster management software for provisioning, orchestration, and monitoring.
  </li>
  <li>
   Telemetry &amp; Observability: Integrate out-of-band management via Redfish/IPMI and in-band telemetry using Prometheus/OpenTelemetry.
  </li>
  <li>
   Infrastructure-as-Code: Develop workflows using MAAS, Terraform, and Ansible for bare-metal and containerized deployments.
  </li>
  <li>
   Kubernetes Orchestration: Enable Kubernetes/Helm-based orchestration for inference clusters and multi-tenancy.
  </li>
  <li>
   Monitoring &amp; Dashboards: Build dashboards for rack health, inventory, and SLA compliance.
  </li>
  <li>
   Continuous Innovation: Stay current with GenAI trends, rack-scale AI orchestration, and data center best practices.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Minimum Qualifications
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Computer Science, Engineering, or related field.
  </li>
  <li>
   5+ years of software engineering experience; 3+ years in ML or HPC environments.
  </li>
  <li>
   Strong programming skills in Python, Rust/Go, and TypeScript, with solid software development fundamentals.
  </li>
  <li>
   Deep understanding of data structures and algorithms in distributed systems and high-performance computing contexts.
  </li>
  <li>
   Hands-on experience with Kubernetes, Helm, Prometheus/OpenTelemetry, and Ansible/Terraform.
  </li>
  <li>
   Practical experience with LLM runtimes, agent frameworks, and rack-scale orchestration.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Preferred Qualifications
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Master&rsquo;s degree in Computer Science, Machine Learning, or related field.
  </li>
  <li>
   Experience building inference and fine-tuning pipelines, as well as agentic workflows.
  </li>
  <li>
   Knowledge of data centre resource lifecycle management, out-of-band protocols (Redfish/IPMI), and MAAS/OpenStack.
  </li>
  <li>
   Exposure to scale-up data centre networking technologies (RoCE/RDMA/NVLink).
  </li>
  <li>
   Contributions to inference and GenAI model performance optimization.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   What's On Offer
   <br/>
   <br/>
  </strong>
 </strong>
 Apart from working with great people, we offer the below:
 <br/>
 <br/>
 <ul>
  <li>
   Salary including housing &amp; transport allowance
  </li>
  <li>
   Stock (RSU's) and performance related bonus
  </li>
  <li>
   16 weeks fully paid Maternity Leave
  </li>
  <li>
   6 weeks fully paid Paternity Leave
  </li>
  <li>
   Employee stock purchase scheme
  </li>
  <li>
   Child Education Allowance
  </li>
  <li>
   Relocation and immigration support (if needed)
  </li>
  <li>
   Life and Medical Insurance
  </li>
  <li>
   Live+ Well Reimbursement for health and recreational membership fees
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Minimum Qualifications:
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 OR
 <br/>
 <br/>
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
 <br/>
 <br/>
 OR
 <br/>
 <br/>
 PhD in Engineering, Information Systems, Computer Science, or related field.
 <br/>
 <br/>
 <ul>
  <li>
   2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.
  </li>
  <li>
   References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
 <br/>
 <br/>
 Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
 <br/>
 <br/>
 <strong>
  To all Staffing and Recruiting Agencies
 </strong>
 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
 <br/>
 <br/>
 If you would like more information about this role, please contact Qualcomm Careers.
</div>


Full Stack Machine Learning Engineer (Datacentre AI Engineering) - Riyadh, KSA

<div>
 <strong>
  Company
  <br/>
  <br/>
 </strong>
 Qualcomm Middle East Information Technology Company LLC
 <br/>
 <br/>
 <strong>
  Job Area
  <br/>
  <br/>
 </strong>
 Engineering Group, Engineering Group &gt; Software Engineering
 <br/>
 <br/>
 <strong>
  General Summary
  <br/>
  <br/>
 </strong>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm&rsquo;s leadership in AI, high‑performance compute, and connectivity is driving innovation across cloud, edge, and data center environments - delivering scalable, power‑efficient platforms that power the next generation of intelligent infrastructure.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 Qualcomm is seeking
 <strong>
  Machine Learning Applications Engineer &ndash; AI Inference &amp; Model Optimization
 </strong>
 to support the enablement of rack-scale deep learning workloads on advanced Qualcomm AI inference accelerators. These accelerators utilize Qualcomm's expertise in hardware-accelerated AI to deliver high-performance, energy-efficient generative AI and computer vision inference solutions for modern data centers.
 <br/>
 <br/>
 This is a
 <strong>
  customer
 </strong>
 ‑
 <strong>
  facing, highly technical role
 </strong>
 focused on
 <strong>
  porting, optimizing, and validating deep learning AI models
 </strong>
 on production systems, and enabling Qualcomm&rsquo;s partners to develop and deploy advanced machine learning applications - including computer vision, speech, generative AI and state of the art multimodal reasoning models - using popular frameworks such as PyTorch, TensorFlow, and ONNX on Qualcomm Cloud AI accelerators. Key responsibilities include evaluating models for throughput, latency, and accuracy; profiling and optimizing model performance; building robust application pipelines; integrating customer frameworks; and contributing to documentation, training, and demonstrations.
 <br/>
 <br/>
 The role requires strong expertise in AI models, quantization, performance optimization, and deployment, plus the ability to shape architecture, workload sizing, and system design. It also requires experience with deep learning model development across hardware platforms, solid programming skills, collaboration with cross-functional teams, and proficiency in machine learning frameworks, Linux, and container orchestration tools.
 <br/>
 <br/>
 The ideal candidate can effectively
 <strong>
  bridge AI model requirements &harr; hardware capabilities &harr; customer expectations
 </strong>
 , guiding customers from
 <strong>
  model selection &rarr; hardware sizing &rarr; deployment decisions &rarr; production readiness.
  <br/>
  <br/>
 </strong>
 <strong>
  What You&rsquo;ll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   AI Model Porting &amp; Optimization
  </li>
  <li>
   Deploy, optimize and scale deep learning AI models onto accelerator‑based data center platforms, including:
  </li>
  <li>
   Model conversion workflows
  </li>
  <li>
   Quantization techniques (INT8 / mixed precision)
  </li>
  <li>
   Runtime integration and optimization
  </li>
  <li>
   Integrate ML models onto Qualcomm&rsquo;s Cloud AI ML stack from frameworks such as PyTorch, TensorFlow, and ONNX.
  </li>
  <li>
   Drive improvements in model throughput, latency, and accuracy, with clear trade‑off analysis.
  </li>
  <li>
   Build, test, and deploy scalable inference pipelines using serving frameworks such as vLLM, TGI, and Triton.
  </li>
  <li>
   Optimize workloads for LLM and GenAI models across both multi-SoC and multi-card architectures.
  </li>
  <li>
   Collaborate with engineering teams to analyze and refine training and inference for advanced deep learning applications.
  </li>
  <li>
   Identify bottlenecks across compute, memory, and runtime, and guide optimization strategies.
  </li>
  <li>
   Contribute to Qualcomm&rsquo;s Cloud AI GitHub repository and developer documentation, sharing technical best practices and solutions.
  </li>
  <li>
   Develop and integrate end-to-end ML application pipelines with customer frameworks and libraries.
  </li>
  <li>
   Customer‑Facing Technical Engagement
  </li>
  <li>
   Act as a trusted technical advisor for customers deploying AI workloads.
  </li>
  <li>
   Engage in hardware sizing and architecture discussions, aligning model requirements with infrastructure capabilities.
  </li>
  <li>
   Provide technical guidance on:
  </li>
  <li>
   AI model selection
  </li>
  <li>
   Deployment feasibility
  </li>
  <li>
   System architecture and performance expectations
  </li>
  <li>
   Lead discussions on model capabilities and limitations based on real customer use cases.
  </li>
  <li>
   Model&ndash;Infrastructure Alignment
  </li>
  <li>
   Assess and evaluate AI model requirements and recommend alternative model approaches when necessary.
  </li>
  <li>
   Align model characteristics (latency, throughput, accuracy) with accelerator and system capabilities.
  </li>
  <li>
   Connect model requirements with:
  </li>
  <li>
   Memory constraints
  </li>
  <li>
   Accelerator architecture
  </li>
  <li>
   Scaling limitations
  </li>
  <li>
   Support customers in defining model selection strategies based on deployment realities.
  </li>
  <li>
   Performance &amp; Scalability Engineering
  </li>
  <li>
   Evaluate performance characteristics of AI models in production scenarios, including:
  </li>
  <li>
   Throughput expectations
  </li>
  <li>
   Latency targets
  </li>
  <li>
   Concurrency behavior
  </li>
  <li>
   Guide architecture decisions around:
  </li>
  <li>
   Scaling strategies (horizontal vs vertical)
  </li>
  <li>
   Hardware deployment sizing
  </li>
  <li>
   Contribute to discussions on:
  </li>
  <li>
   Workload scalability limits
  </li>
  <li>
   Impact of model selection on system performance and efficiency
  </li>
  <li>
   Provide insights into capacity planning and infrastructure optimization.
  </li>
  <li>
   End‑to‑End AI Pipeline Design
  </li>
  <li>
   Drive discussions around end‑to‑end AI pipelines, including:
  </li>
  <li>
   Multi‑model workflows (e.g., detection + tracking + recognition)
  </li>
  <li>
   Data preprocessing and post‑processing stages
  </li>
  <li>
   Guide decisions on video and data processing stacks, including:
  </li>
  <li>
   Video pipeline choices (e.g., FFMPEG vs GStreamer)
  </li>
  <li>
   Integration into inference pipelines
  </li>
  <li>
   Ensure pipelines are aligned with:
  </li>
  <li>
   Performance requirements
  </li>
  <li>
   Hardware capabilities
  </li>
  <li>
   Real‑time constraints
  </li>
  <li>
   Model Trade‑off Analysis &amp; Validation
  </li>
  <li>
   Highlight and explain trade‑offs between:
  </li>
  <li>
   Accuracy vs compatibility
  </li>
  <li>
   Model quality vs deployment feasibility
  </li>
  <li>
   Support decision‑making on:
  </li>
  <li>
   Model simplification vs performance gains
  </li>
  <li>
   Precision vs efficiency trade‑offs
  </li>
  <li>
   Lead or support model capability validation in deployment environments.
  </li>
  <li>
   Collaborate with customers to define:
  </li>
  <li>
   Inference assumptions
  </li>
  <li>
   Model sizing strategies for large‑scale workloads
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
  </li>
  <li>
   10&ndash;15+ years of experience in:
  </li>
  <li>
   Deep learning model development or deployment experience on CPUs/GPUs/ASICs.
  </li>
  <li>
   Inference systems and optimization
  </li>
  <li>
   Data center or edge AI platforms
  </li>
  <li>
   Strong experience with:
  </li>
  <li>
   Model quantization and optimization techniques
  </li>
  <li>
   AI model frameworks (e.g., PyTorch, TensorFlow)
  </li>
  <li>
   Model deployment pipelines
  </li>
  <li>
   Excellent C/C++/Python programming and software design skills, including debugging, and performance analysis.
  </li>
  <li>
   Hands on expertise with Linux-based systems, low level software, drivers, and system bring up.
  </li>
  <li>
   Proven ability to analyze and optimize model performance in production environments.
  </li>
  <li>
   Solid understanding of:
  </li>
  <li>
   AI inference hardware constraints
  </li>
  <li>
   System level performance bottlenecks
  </li>
  <li>
   Strong communication skills and experience in customer facing technical roles.
  </li>
  <li>
   Willingness to travel for customer engagements and strategic reviews.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Skilled in deploying models on platforms that use hardware accelerators for inference.
  </li>
  <li>
   Experienced with managing multi-model workflows and building real-time AI systems, including computer vision, video, and analytics projects.
  </li>
  <li>
   Knowledgeable about distributed inference methods and handling large-scale model deployments.
  </li>
  <li>
   Proficient in developing and maintaining video processing workflows and using relevant software frameworks.
  </li>
  <li>
   Deep understanding of how system-level decisions affect performance in actual deployment environments.
  </li>
  <li>
   Capable of simplifying complex technical ideas into straightforward, useful advice for clients.
  </li>
  <li>
   Hands-on experience running deep learning models on popular ML frameworks such as PyTorch, TensorFlow, ONNX
  </li>
  <li>
   Experience developing software solutions that run in Linux environments with containers and orchestration
  </li>
  <li>
   Experience with Source code and configuration management tools, Git knowledge is required.
  </li>
  <li>
   Customer-facing experience translating customer requirements into technical solutions (discovery, scoping, success criteria, and execution plans).
  </li>
  <li>
   Proven ability to build and deliver technical demos, proofs-of-concept, and reference applications for ML/GenAI workloads.
  </li>
  <li>
   Strong technical writing skills to produce customer-ready documentation (getting started guides, deployment runbooks, troubleshooting guides) and deliver partner training sessions.
  </li>
  <li>
   Experience driving issue triage and technical escalations with customers, coordinating across product, hardware, and software engineering teams to resolution.
  </li>
  <li>
   Excellent stakeholder management and communication skills: present complex technical concepts clearly to both engineering and non-engineering audiences.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Qualcomm
  <br/>
  <br/>
 </strong>
 At Qualcomm, you&rsquo;ll work at the intersection of
 <strong>
  AI silicon, system architecture, and real
 </strong>
 ‑
 <strong>
  world deployment
 </strong>
 . You will engage directly with strategic customers, influence next‑generation AI data center platforms, and help define scalable, power‑efficient infrastructure for the AI era. This role provides a unique opportunity to shape both
 <strong>
  technology direction and customer outcomes
 </strong>
 , while working with world‑class engineering and product teams.
 <br/>
 <br/>
 <strong>
  What's On Offer
  <br/>
  <br/>
 </strong>
 Apart from working with great people, we offer the below:
 <br/>
 <br/>
 <ul>
  <li>
   Salary including housing &amp; transport allowance
  </li>
  <li>
   Stock (RSU's) and performance related bonus
  </li>
  <li>
   16 weeks fully paid Maternity Leave
  </li>
  <li>
   6 weeks fully paid Paternity Leave
  </li>
  <li>
   Employee stock purchase scheme
  </li>
  <li>
   Child Education Allowance
  </li>
  <li>
   Relocation and immigration support (if needed)
  </li>
  <li>
   Life and Medical Insurance
  </li>
  <li>
   Live+ Well Reimbursement for health and recreational membership fees
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Minimum Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 OR
 <br/>
 <br/>
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Engineering or related work experience.
 <br/>
 <br/>
 OR
 <br/>
 <br/>
 PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
 <br/>
 <br/>
 <ul>
  <li>
   3+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
  </li>
  <li>
   References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
 <br/>
 <br/>
 Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
 <br/>
 <br/>
 <strong>
  To all Staffing and Recruiting Agencies
 </strong>
 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
 <br/>
 <br/>
 If you would like more information about this role, please contact Qualcomm Careers.
</div>


ML Application Engineer – AI Inference & Model Optimization (Staff/Senior Staff level) - Riyadh, KSA

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Middle East Information Technology Company LLC
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Engineering Group, Engineering Group &gt; Software Engineering
<p></p><p><b>General Summary:
</b></p><p></p><div><div><p><b>About Us
</b></p></div><div><p>Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm&rsquo;s leadership in AI, high ‑ performance compute, and connectivity is driving innovation across cloud, edge, and data center environments - delivering scalable, power ‑ efficient platforms that power the next generation of intelligent infrastructure.<br>
</p></div><p></p><div><p><b>About the Role
</b></p></div><div><p>Qualcomm is seeking a <b>Machine Learning Operations &amp; Customer Support Engineer </b>within the Customer Engineering team to support strategic customers deploying AI inference workloads on advanced Qualcomm AI inference accelerator s . These accelerators utilize Qualcomm's expertise in hardware-accelerated AI to deliver high-performance, energy-efficient generative AI and computer vision inference solutions for modern data centers.
</p></div><p></p><div><p>This is a <b>customer-facing, production-critical role </b>focused on ensuring maximum system uptime, reliability, and performance, while resolving customer support cases within defined SLAs/KPIs. The role requires deep expertise across ML inference pipelines, systems troubleshooting , and data center operations, working closely with customers, internal engineering, and product teams.
</p></div><div><p>The i deal candidate will bring a strong foundation in ML model deployment, systems engineering, rack-scale management software, DevOps/ MLOps automation, and cross functional collaboration.<br>
</p></div><p></p><div><p><b>What You&rsquo;ll Do
</b></p></div><div><p><b>Customer Support &amp; SLA Ownership
</b></p></div><div><ul><li>Act as the primary technical escalation point for customer issues related to AI inference workloads
</li></ul></div><div><ul><li>Own end-to-end case management, ensuring resolution within agreed SLAs and KPIs
</li></ul></div><div><ul><li><p>Drive incident response, triage, and root cause analysis (RCA) .
</p></li></ul></div><div><ul><li><p>Provide timely and transparent communication to customers on issue status and resolution
</p></li></ul></div><div><ul><li><p>Maintain high levels of customer satisfaction and service reliability
</p></li></ul></div><p></p><div><p><b>Uptime, Reliability &amp; Operations
</b></p></div><div><ul><li><p>Ensure high availability and uptime of customer AI deployments (rack-scale systems)
</p></li></ul></div><div><ul><li><p>Monitor system health, performance metrics, and workload behavior
</p></li></ul></div></div><div><div><ul><li><p>Implement and manage failover, redundancy, and resiliency mechanisms
</p></li></ul></div><div><ul><li><p>Proactively identify risks and implement preventative actions
</p></li></ul></div><p></p><div><p><b>AI Inference Workload Support
</b></p></div><div><ul><li><p>Support deployment, optimization, and troubleshooting of ML inference pipelines
</p></li></ul></div><div><ul><li><p>Debug issues across model, runtime, system, and hardware layers
</p></li></ul></div><div><ul><li><p>Analyze model performance (latency, throughput, accuracy tradeoffs) in production
</p></li></ul></div><div><ul><li><p>Support frameworks such as PyTorch , TensorFlow, ONNX, and model conversion flows
</p></li></ul></div><div><ul><li><p>Assist in model optimization techniques (quantization, batching, compilation, runtime tuning)
</p></li></ul></div><p></p><div><p><b>System &amp; Infrastructure Engineering
</b></p></div><div><ul><li><p>Support bare-metal and virtualized environments for AI workloads
</p></li></ul></div><div><ul><li><p>Troubleshoot issues across Linux OS, drivers, firmware, and networking stack
</p></li></ul></div><div><ul><li><p>Support deployment and maintenance using Infrastructure as Code ( IaC ) and automation tools
</p></li></ul></div><div><ul><li><p>Work with DCIM tools and monitoring systems for infrastructure visibility
</p></li></ul></div><div><ul><li><p>Coordinate with hardware vendors for accelerator, server, and networking issues
</p></li></ul></div><p></p><div><p><b>Monitoring, Observability &amp; Automation
</b></p></div><div><ul><li><p>Implement and manage monitoring systems (logs, metrics, traces)
</p></li></ul></div><div><ul><li><p>Build dashboards for uptime, SLA adherence, performance, and utilization
</p></li></ul></div><div><ul><li><p>Automate repetitive operational tasks using scripts and workflows
</p></li></ul></div><div><ul><li><p>Establish and enforce runbooks and standard operating procedures (SOPs)
</p></li></ul></div><p></p><div><p><b>Cross-Functional Collaboration
</b></p></div></div><div><div><ul><li><p>Work closely with Customer Engineering, Product, Engineering, and Support teams
</p></li></ul></div><div><ul><li><p>Provide structured feedback to engineering for product improvements and defect resolution
</p></li></ul></div><div><ul><li><p>Support customer onboarding, deployment readiness, and operational handover
</p></li></ul></div><div><ul><li><p>Participate in customer reviews, escalations, and technical deep dives<br>
</p></li></ul></div><p></p><div><p><b>Required Qualifications
</b></p></div><div><ul><li><p>Bachelor&rsquo;s degree in Computer Science , Computer Engineering, Electrical Engineering, or related field
</p></li></ul></div><div><ul><li><p>10&ndash;15+ years of experience in ML operations, systems engineering, or customer support engineering
</p></li></ul></div><div><ul><li><p>Proven experience in customer-facing technical roles with SLA-driven support models
</p></li></ul></div><div><ul><li><p>Strong experience with AI/ML inference workloads in production environments
</p></li></ul></div><div><ul><li><p>Deep understanding of end-to-end ML inference pipelines
</p></li></ul></div><div><ul><li><p>Hands-on experience with Linux systems, system bring-up, drivers, and debugging tools
</p></li></ul></div><div><ul><li><p>Strong understanding of AI accelerator architecture and system bottlenecks
</p></li></ul></div><div><ul><li><p>Experience with model deployment, optimization, and performance tuning
</p></li></ul></div><div><ul><li><p>Experience with data center operations and rack-scale deployments
</p></li></ul></div><div><ul><li><p>Familiarity with bare-metal, virtualization, and containerization technologies (Docker, Kubernetes)
</p></li></ul></div><div><ul><li><p>Knowledge of networking concepts (TCP/IP, RDMA, storage systems)
</p></li></ul></div><div><ul><li><p>Experience with cloud and hybrid environments
</p></li></ul></div><div><ul><li><p>Experience with monitoring/observability tools (Prometheus, Grafana, ELK, etc.)
</p></li></ul></div><div><ul><li><p>Strong skills in incident management, RCA, and production operations
</p></li></ul></div></div><div><div><ul><li><p>Experience defining and tracking SLAs, KPIs, and operational metrics
</p></li></ul></div><div><ul><li><p>Proficiency in Python, Bash, or similar scripting languages
</p></li></ul></div><div><ul><li><p>Experience in automation, DevOps, and MLOps tooling
</p></li></ul></div><div><ul><li><p>Strong problem-solving and diagnostic skills
</p></li></ul></div><div><ul><li><p>Excellent communication and customer engagement skills
</p></li></ul></div><div><ul><li><p>Ability to operate in high-pressure, mission-critical environments
</p></li></ul></div><div><ul><li><p>High attention to detail with a focus on quality, reliability, and accountability
</p></li></ul></div><p></p><div><p><b>Preferred Qualifications
</b></p></div><div><ul><li><p>Experience with Qualcomm Cloud AI or similar AI accelerator platforms
</p></li></ul></div><div><ul><li><p>Experience supporting large-scale AI deployments (LLMs, CV pipelines, generative AI)
</p></li></ul></div><div><ul><li><p>Familiarity with inference runtimes ( TensorRT , ONNX Runtime, custom runtimes)
</p></li></ul></div><div><ul><li><p>Experience with CI/CD pipelines for ML deployment<br>
</p></li></ul></div><p></p><div><p><b>Why Join Qualcomm
</b></p></div><div><p>At Qualcomm, you&rsquo;ll work at the intersection of <b>AI silicon, system architecture, and real </b>‑ <b>world deployment </b>. You will engage directly with strategic customers, influence next ‑ generation AI data center platforms, and help define scalable, power ‑ efficient infrastructure for the AI era. This role provides a unique opportunity to shape both <b>technology direction and customer outcomes </b>, while working with world ‑ class engineering and product teams.
</p><p></p><p><b>What's on Offer
</b></p><p>Apart from working with great people, we offer the below:
</p><ul><li><p>Salary including housing &amp; transport allowance
</p></li><li><p>Stock (RSU's) and performance related bonus
</p></li><li><p>16 weeks fully paid Maternity Leave
</p></li><li><p>6 weeks fully paid Paternity Leave
</p></li><li><p>Employee stock purchase scheme
</p></li><li><p>Child Education Allowance
</p></li><li><p>Relocation and immigration support (if needed)
</p></li><li><p>Life and Medical Insurance
</p></li><li><p>Live+ Well Reimbursement for health and recreational membership fees
</p></li></ul></div></div><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
</li></ul>OR
<br>
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
<br>
OR
<br>
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
<br>
<br>
<ul><li>2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul><p></p><p>*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
</p><p></p><div><p>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</p></div><p></p><p>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
</p><p></p><p><b>To all Staffing and Recruiting Agencies </b>: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

ML Operations & Customer Support Engineer, Staff/Senior Staff level - Riyadh, KSA

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Middle East Information Technology Company LLC
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Engineering Group, Engineering Group &gt; Software Engineering
<p></p><p><b>General Summary:
</b></p><p></p><div><div><p><b>About Us
</b></p></div><div><p>Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm&rsquo;s leadership in AI, high ‑ performance compute, and connectivity is driving innovation across cloud, edge, and data center environments - delivering scalable, power ‑ efficient platforms that power the next generation of intelligent infrastructure.<br>
</p></div><p></p><div><p><b>About the Role
</b></p></div><div><p>Qualcomm is seeking <b>Machine Learning Applications Engineer </b><b>&ndash; AI </b><b>Inference &amp; Model Optimization </b>to support the enablement of rack-scale deep learning workloads on advanced Qualcomm AI inference accelerator s . These accelerators utilize Qualcomm's expertise in hardware-accelerated AI to deliver high-performance, energy-efficient generative AI and computer vision inference solutions for modern data centers.
</p></div><p></p><div><p>This is a <b>customer </b>‑ <b>facing, highly technical role </b>focused on <b>porting, optimizing, and validating </b><b>deep learning </b><b>AI models </b>on production systems, and enabling Qualcomm&rsquo;s partners to develop and deploy advanced machine learning applications - including computer vision, speech, generative AI and state of the art multimodal reasoning models - using popular frameworks such as PyTorch , TensorFlow, and ONNX on Qualcomm Cloud AI accelerators. Key responsibilities include evaluating models for throughput, latency, and accuracy; profiling and optimizing model performance; building robust application pipelines; integrating customer frameworks; and contributing to documentation, training, and demonstrations.
</p></div><p></p><div><p>The role requires strong expertise in AI models, quantization, performance optimization, and deployment, plus the ability to shape architecture, workload sizing, and system design. It also requires experience with deep learning model development across hardware platforms, solid programming skills, collaboration with cross-functional teams, and proficiency in machine learning frameworks, Linux, and container orchestration tools.
</p></div><p></p><div><p>The ideal candidate can effectively <b>bridge AI model requirements hardware capabilities customer expectations </b>, guiding customers from <b>model selection hardware sizing deployment decisions production readiness.
</b></p></div><p></p><div><p><b>What You&rsquo;ll Do
</b></p></div><div><p><b>A) AI Model Porting &amp; Optimization
</b></p></div><div><ul><li><p>Deploy, optimize and scale deep learning AI models onto accelerator ‑ based data center platforms, including:
</p></li></ul></div><div><ul><li><p>Model conversion workflows
</p></li></ul></div><div><ul><li><p>Quantization techniques (INT8 / mixed precision)
</p></li></ul></div><div><ul><li><p>Runtime integration and optimization
</p></li></ul></div><div><ul><li><p>Integrate ML models onto Qualcomm&rsquo;s Cloud AI ML stack from frameworks such as PyTorch , TensorFlow, and ONNX.
</p></li></ul></div><div><ul><li><p>Drive improvements in <b>model </b><b>throughput </b><b>, </b><b>latency </b><b>, and accuracy </b>, with clear trade ‑ off analysis.
</p></li></ul></div><div><ul><li><p>Build, test, and deploy scalable inference pipelines using serving frameworks such as vLLM , TGI, and Triton.
</p></li></ul></div><div><ul><li><p>Optimize workloads for LLM and GenAI models across both multi-SoC and multi-card architectures.
</p></li></ul></div></div><div><div><ul><li><p>Collaborate with engineering teams to analyze and refine training and inference for advanced deep learning applications.
</p></li></ul></div><div><ul><li><p>Identify bottlenecks across compute, memory, and runtime, and guide optimization strategies.
</p></li></ul></div><div><ul><li><p>Contribute to Qualcomm&rsquo;s Cloud AI GitHub repository and developer documentation, sharing technical best practices and solutions.
</p></li></ul></div><div><ul><li><p>Develop and integrate end-to-end ML application pipelines with customer frameworks and libraries.<br>
</p></li></ul></div><p></p><div><p><b>B) Customer </b>‑ <b>Facing Technical Engagement
</b></p></div><div><ul><li><p>Act as a <b>trusted technical advisor </b>for customers deploying AI workloads.
</p></li></ul></div><div><ul><li><p>Engage in <b>hardware sizing and architecture discussions </b>, aligning model requirements with infrastructure capabilities.
</p></li></ul></div><div><ul><li><p>Provide technical guidance on:
</p></li></ul></div><div><ul><li><p>AI model selection
</p></li></ul></div><div><ul><li><p>Deployment feasibility
</p></li></ul></div><div><ul><li><p>System architecture and performance expectations
</p></li></ul></div><div><ul><li><p>Lead discussions on <b>model capabilities and limitations </b>based on real customer use cases.<br>
</p></li></ul></div><p></p><div><p><b>C) Model&ndash;Infrastructure Alignment
</b></p></div><div><ul><li><p>Assess and evaluate AI model requirements and recommend <b>alternative model approaches </b>when necessary.
</p></li></ul></div><div><ul><li><p>Align model characteristics (latency, throughput, accuracy) with <b>accelerator and system capabilities </b>.
</p></li></ul></div><div><ul><li><p>Connect <b>model requirements </b>with:
</p></li></ul></div><div><ul><li><p>Memory constraints
</p></li></ul></div></div><div><div><ul><li><p>Accelerator architecture
</p></li></ul></div><div><ul><li><p>Scaling limitations
</p></li></ul></div><div><ul><li><p>Support customers in defining <b>model selection strategies based on deployment realities </b>.<br>
</p></li></ul></div><p></p><div><p><b>D) Performance &amp; Scalability Engineering
</b></p></div><div><ul><li><p>Evaluate performance characteristics of AI models in production scenarios, including:
</p></li></ul></div><div><ul><li><p>Throughput expectations
</p></li></ul></div><div><ul><li><p>Latency targets
</p></li></ul></div><div><ul><li><p>Concurrency behavior
</p></li></ul></div><div><ul><li><p>Guide architecture decisions around:
</p></li></ul></div><div><ul><li><p>Scaling strategies (horizontal vs vertical)
</p></li></ul></div><div><ul><li><p>Hardware deployment sizing
</p></li></ul></div><div><ul><li><p>Contribute to discussions on:
</p></li></ul></div><div><ul><li><p>Workload scalability limits
</p></li></ul></div><div><ul><li><p>Impact of model selection on system performance and efficiency
</p></li></ul></div><div><ul><li><p>Provide insights into <b>capacity planning and infrastructure optimization </b>.<br>
</p></li></ul></div><p></p><div><p><b>E) End </b>‑ <b>to </b>‑ <b>End AI Pipeline Design
</b></p></div><div><ul><li><p>Drive discussions around <b>end </b>‑ <b>to </b>‑ <b>end AI pipelines </b>, including:
</p></li></ul></div><div><ul><li><p>Multi ‑ model workflows (e.g., detection + tracking + recognition)
</p></li></ul></div></div><div><div><ul><li><p>Data preprocessing and post ‑ processing stages
</p></li></ul></div><div><ul><li><p>Guide decisions on video and data processing stacks, including:
</p></li></ul></div><div><ul><li><p>Video pipeline choices (e.g., FFMPEG vs GStreamer )
</p></li></ul></div><div><ul><li><p>Integration into inference pipelines
</p></li></ul></div><div><ul><li><p>Ensure pipelines are aligned with:
</p></li></ul></div><div><ul><li><p>Performance requirements
</p></li></ul></div><div><ul><li><p>Hardware capabilities
</p></li></ul></div><div><ul><li><p>Real ‑ time constraints<br>
</p></li></ul></div><p></p><div><p><b>F) Model Trade </b>‑ <b>off Analysis &amp; Validation
</b></p></div><div><ul><li><p>Highlight and explain trade ‑ offs between:
</p></li></ul></div><div><ul><li><p>Accuracy vs compatibility
</p></li></ul></div><div><ul><li><p>Model quality vs deployment feasibility
</p></li></ul></div><div><ul><li><p>Support decision ‑ making on:
</p></li></ul></div><div><ul><li><p>Model simplification vs performance gains
</p></li></ul></div><div><ul><li><p>Precision vs efficiency trade ‑ offs
</p></li></ul></div><div><ul><li><p>Lead or support <b>model capability validation </b>in deployment environments.
</p></li></ul></div><div><ul><li><p>Collaborate with customers to define:
</p></li></ul></div><div><ul><li><p>Inference assumptions
</p></li></ul></div><div><ul><li><p>Model sizing strategies for large ‑ scale workloads<br>
</p></li></ul></div></div><p></p><div><div><p><b>Required Qualifications
</b></p></div><div><ul><li><p>Bachelor&rsquo;s degree in Computer Science , Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
</p></li></ul></div><div><ul><li><p>10&ndash;15+ years of experience in:
</p></li></ul></div><div><ul><li><p>D eep learning model development or deployment experience on CPUs/GPUs/ASICs.
</p></li></ul></div><div><ul><li><p>Inference systems and optimization
</p></li></ul></div><div><ul><li><p>Data center or edge AI platforms
</p></li></ul></div><div><ul><li><p>Strong experience with:
</p></li></ul></div><div><ul><li><p>Model quantization and optimization techniques
</p></li></ul></div><div><ul><li><p>AI model frameworks (e.g., PyTorch , TensorFlow)
</p></li></ul></div><div><ul><li><p>Model deployment pipelines
</p></li></ul></div><div><ul><li><p>Excellent C/C++/Python programming and software design skills, including debugging, and performance analysis.
</p></li></ul></div><div><ul><li><p>Hands on expertise with Linux-based systems, low level software, drivers, and system bring up.
</p></li></ul></div><div><ul><li><p>Proven ability to analyze and optimize model performance in production environments.
</p></li></ul></div><div><ul><li><p>Solid understanding of:
</p></li></ul></div><div><ul><li><p>AI inference hardware constraints
</p></li></ul></div><div><ul><li><p>System level performance bottlenecks
</p></li></ul></div><div><ul><li><p>Strong communication skills and experience in customer facing technical roles.
</p></li></ul></div><div><ul><li><p>Willingness to travel for customer engagements and strategic reviews.<br>
</p></li></ul></div></div><p></p><div><div><p><b>Preferred Qualifications
</b></p></div><div><ul><li><p>Skilled in deploying models on platforms that use hardware accelerators for inference.
</p></li></ul></div><div><ul><li><p>Experienced with managing multi-model workflows and building real-time AI systems, including computer vision, video, and analytics projects.
</p></li></ul></div><div><ul><li><p>Knowledgeable about distributed inference methods and handling large-scale model deployments.
</p></li></ul></div><div><ul><li><p>Proficient in developing and maintaining video processing workflows and using relevant software frameworks.
</p></li></ul></div><div><ul><li><p>Deep understanding of how system-level decisions affect performance in actual deployment environments.
</p></li></ul></div><div><ul><li><p>Capable of simplifying complex technical ideas into straightforward, useful advice for clients.
</p></li></ul></div><div><ul><li><p>Hands-on experience running deep learning models on popular ML frameworks such as PyTorch , TensorFlow, ONNX
</p></li></ul></div><div><ul><li><p>Experience developing software solutions that run in Linux environments with containers and orchestration
</p></li></ul></div><div><ul><li><p>Experience with Source code and configuration management tools, Git knowledge is required.
</p></li></ul></div><div><ul><li><p>Customer-facing experience translating customer requirements into technical solutions (discovery, scoping, success criteria, and execution plans).
</p></li></ul></div><div><ul><li><p>Proven ability to build and deliver technical demos, proofs-of-concept, and reference applications for ML/GenAI workloads.
</p></li></ul></div><div><ul><li><p>Strong technical writing skills to produce customer-ready documentation (getting started guides, deployment runbooks, troubleshooting guides) and deliver partner training sessions.
</p></li></ul></div><div><ul><li><p>Experience driving issue triage and technical escalations with customers, coordinating across product , hardware, and software engineering teams to resolution.
</p></li></ul></div><div><ul><li><p>Excellent stakeholder management and communication skills: present complex technical concepts clearly to both engineering and non-engineering audiences.<br>
</p></li></ul></div></div><p></p><div><p><b>Why Join Qualcomm
</b></p></div><div><p>At Qualcomm, you&rsquo;ll work at the intersection of <b>AI silicon, system architecture, and real </b>‑ <b>world deployment </b>. You will engage directly with strategic customers, influence next ‑ generation AI data center platforms, and help define scalable, power ‑ efficient infrastructure for the AI era. This role provides a unique opportunity to shape both <b>technology direction and customer outcomes </b>, while working with world ‑ class engineering and product teams.
</p><p></p><p><b>What's on Offer
</b></p><p>Apart from working with great people, we offer the below:
</p><ul><li><p>Salary including housing &amp; transport allowance
</p></li><li><p>Stock (RSU's) and performance related bonus
</p></li><li><p>16 weeks fully paid Maternity Leave
</p></li><li><p>6 weeks fully paid Paternity Leave
</p></li><li><p>Employee stock purchase scheme
</p></li><li><p>Child Education Allowance
</p></li><li><p>Relocation and immigration support (if needed)
</p></li><li><p>Life and Medical Insurance
</p></li><li><p>Live+ Well Reimbursement for health and recreational membership fees
</p></li></ul></div><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.
</li></ul>OR
<br>
Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Engineering or related work experience.
<br>
OR
<br>
PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
<br>
<br>
<ul><li>3+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul><p></p><p>*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
</p><p></p><div><p>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</p></div><p></p><p>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
</p><p></p><p><b>To all Staffing and Recruiting Agencies </b>: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

AI Platform & Inference Suite Engineer (Staff/Senior Staff level) - Riyadh, KSA

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