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TAWANTECH

<div><p><b>Job Summary</b></p><p>
We are seeking an AI Software Engineer with hands-on experience in Large Language Models (LLMs) and Generative AI technologies to develop intelligent solutions that enhance customer experience, operational efficiency, and knowledge management within the banking sector.</p><p></p><p><b>
Key Responsibilities</b></p><ul><li>Design, develop, and deploy AI-powered applications leveraging LLMs and Generative AI.</li><li>Build Retrieval-Augmented Generation (RAG) solutions using enterprise banking data.</li><li>Develop intelligent assistants, chatbots, and knowledge management solutions.</li><li>Integrate AI services with banking applications and APIs.</li><li>Fine-tune, evaluate, and optimize LLM performance.</li><li>Ensure compliance with banking security, governance, and regulatory requirements.</li><li>Collaborate with business, data, and technology teams to deliver AI-driven solutions.</li></ul><b><br>
Requirements</b><ul><li><br>
4+ years of software engineering experience.</li><li>Strong Python programming skills.</li><li>Experience with LLMs, Generative AI, and Prompt Engineering.</li><li>Experience with LangChain, LlamaIndex, Vector Databases, and RAG architectures.</li><li>Familiarity with machine learning frameworks and AI deployment practices.</li><li>Experience with cloud platforms (AWS, Azure, GCP) is preferred.</li></ul><p></p><p><b>
Preferred Qualifications</b></p><ul><li>Banking or Financial Services experience.</li><li>Experience developing AI copilots or customer-facing AI solutions.</li><li>Knowledge of AI governance and responsible AI practices.</li></ul></div>

AI Software Engineer / LLM Engineer

FileCloud

<div><p>FileCloud is looking for an enthusiastic<b> Senior PHP Backend Developer to join our team in Riyadh, Kingdom of Saudi Arabia.</b> As part of the Growth &amp; Expansion team, you will be responsible for developing server-side functionality and building scalable cloud-based services. We are looking for a mid-level or senior developer. This role is fully office-based and will require working in our office in Riyadh and connecting with the wider, global FileCloud team</p>
<p><b>
About the Product &amp; Company:</b>
</p><p>FileCloud is a hyper-secure EFSS (enterprise file sync and share) platform that provides industry leading compliance, data governance, data leak protection, data retention and digital rights management capabilities. FileCloud is a leader in content governance and collaboration for unstructured data, trusted and used worldwide across Global 1000 enterprises, educational institutions, government organizations, and service providers. In addition to its enterprise file sharing solution, FileCloud&rsquo;s product portfolio also includes Signority (acquired in May 2024), a Canadian-based e-signature and document workflow platform. We are currently expanding our team as we grow and improve FileCloud.
</p><p><b>Responsibilities:</b>
</p><ul><li>Create elegant, efficient and bulletproof software to support and extend our current software products</li>
<li>Use tools including PHPStorm, MongoDB, NodeJS, AWS/AZURE, GIT, Memcache, Code Reviews, PHPUnit, Solr, among others</li>
<li>Solve complex architectural challenges when implementing new features</li>
<li>Integrate with databases, file systems, cloud services when delivering solutions</li>
<li>Troubleshoot and fix reported customer issues, delivering software patches as needed
</li><li>Share your knowledge and experience with other engineers</li>
</ul>
<p><b>Qualifications:</b>
</p><ul><li>4+ years of professional software engineering experience
</li><li>3+ years of experience in web app development
</li><li>3+ years in PHP development
</li><li>Strong knowledge of the following:
</li><li>Automation testing</li>
<li>Client server architecture is required</li>
<li>Object-oriented programming and design patterns</li>
<li>PHP ecosystems (PHP 8.2+ experience, Composer, PHPUnit)</li>
<li>Web technologies including HTTP protocol, XML, REST</li>
<li>Highly proficient in spoken and written English with strong communication skills
</li><li>Comfortable using AI coding assistants (e.g. Claude Code, GitHub Copilot, Cursor, or similar) as part of a daily development workflow - for code generation, review, debugging, and documentation.</li>
</ul>
<p> <b>Nice-to-Have:</b>
</p><ul><li>Bachelor&rsquo;s degree in computer science or a related discipline</li>
<li>Knowledge of modern PHP frameworks</li>
<li>Experience in enterprise system&rsquo;s architecture (Architecture Patterns, Eventing, Queues)</li>
<li>Familiarity with SQL/NoSQL databases like MongoDB and their declarative query languages</li>
<li>Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3</li>
<li>Knowledge of CI/CD (Jenkins preferred), Docker, SOLR, Redis</li>
<li>Experience developing with NodeJS, JavaScript, TypeScript.</li>
</ul>
<p><b>What We Offer &ndash; These Do not change</b>
</p><ul><li>Be part of a team of passionate, committed individuals dedicated to building a world-class product
</li><li>Dedicated time for training and education opportunities
</li><li>A mentorship model wherein your mentor and team support your development
</li><li>A competitive salary with an annual bonus
</li><li>Onsite work with flexible hours that fall outside of 9am -12pm (US Eastern Standard Time)</li>
<li>20 days of paid time off, which increases by a further 2 days after 3 years of service and 3 days after 5 years of service (in addition to 10 public holidays in your country)
</li><li>Paid day off on your birthday or on an alternative day if your birthday falls outside a typical working day
</li><li>Paid day off to volunteer with the charity of your choice
</li><li>Paid monthly internet cost, as well as lunch and a wellbeing stipend provided
</li><li>Reimbursement of all hardware costs associated with the role</li>
</ul>
<p>Please note that we conduct background security checks for everyone joining our team.</p>
<p>
<i> </i>AI-assisted screening may be used during the application review process.</p></div>

Senior PHP Backend Developer (Riyadh, KSA)

Qualcomm

<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 growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region
 <strong>
  .
 </strong>
 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>
  About The Role
  <br/>
  <br/>
 </strong>
 We are seeking a Staff‑level ML Applications Engineer with deep hands‑on experience in C++/Python‑based AI development in a Linux environment. The ideal candidate operates with a high degree of autonomy, defines technical goals and scope for assigned problem areas, and leads development efforts through execution. This role requires strong analytical skills, effective cross‑team collaboration, and the ability to mentor and guide other engineers by example while remaining hands‑on and execution‑focused.
 <br/>
 <br/>
 <strong>
  We are looking for 8+ years Software Engineering or related work experience
  <br/>
  <br/>
 </strong>
 <strong>
  Key Responsibilities Will Include
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Improve and optimize key Deep Learning models on Qualcomm AI 100
  </li>
  <li>
   Build deep learning framework extensions for Qualcomm AI 100 in upstream open-source repositories
  </li>
  <li>
   Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning
  </li>
  <li>
   Build software tools and ecosystem around AI SW Stack.
  </li>
  <li>
   Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator.
  </li>
  <li>
   Optimize workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems
  </li>
  <li>
   Optimize the entire deep learning pipeline including graph compiler integration
  </li>
  <li>
   Apply knowledge of software engineering best practices.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Desirable Skills And Aptitudes
  <br/>
  <br/>
 </strong>
 <strong>
  Required Skills and Aptitude
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Deep Learning experience or knowledge &ndash; LLMs, Natural Language Processing, Vision, Audio, Recommendation systems
  </li>
  <li>
   Excellent C/C++ Or Python programming and software design skills, including debugging, performance analysis, and test design.
  </li>
  <li>
   Very strong hold on Pytorch and JIT.
  </li>
  <li>
   Well versed with open-source development practices.
  </li>
  <li>
   Ability to work independently, define requirements and scope, and lead a development effort.
  </li>
  <li>
   Mentors and guides team members through influence and example, without direct people‑management responsibility
  </li>
  <li>
   Avid problem solver &ndash; should be able to find solutions to key engineering and domain problems.
  </li>
  <li>
   Strong developer with a research mindset &ndash; strives to innovate.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Skills
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experiences to run workloads on large scale heterogeneous clusters is a plus
  </li>
  <li>
   Knowledge of compiler is a plus.
  </li>
  <li>
   Hands-on experience with CUDA, CUDNN is a plus.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's / Masters/ PHD degree in Engineering, Machine learning/ AI, Information Systems, Computer Science, or related field.
  </li>
  <li>
   8+ years Software Engineering or related work experience.
  </li>
  <li>
   2+ years experience with Programming Language such as C++, Python.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <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 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>


Machine Learning Engineer, Staff level (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 <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>

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