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ai inference engineer

Qualcomm

<div>
 
 Company
 
 
 
 Qualcomm Middle East Information Technology Company LLC
 
 
 
 Job Area
 
 
 
 Engineering Group, Engineering Group &gt; Software Engineering
 
 
 
 General Summary
 
 
 
 
 About Us
 
 
 
 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.
 
 
 
 About The Role
 
 
 
 Qualcomm is seeking a
 
 Machine Learning Operations &amp; Customer Support Engineer
 
 within the Customer Engineering team to support strategic customers deploying AI inference 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.
 
 
 This is a
 
 customer-facing, production-critical role
 
 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.
 
 
 The ideal candidate will bring a strong foundation in ML model deployment, systems engineering, rack-scale management software, DevOps/MLOps automation, and cross functional collaboration.
 
 
 
 What You&rsquo;ll Do
 
 
 
 
 Customer Support &amp; SLA Ownership
 
 
 
 <ul>
 <li>
 Act as the primary technical escalation point for customer issues related to AI inference workloads
 </li>
 <li>
 Own end-to-end case management, ensuring resolution within agreed SLAs and KPIs
 </li>
 <li>
 Drive incident response, triage, and root cause analysis (RCA).
 </li>
 <li>
 Provide timely and transparent communication to customers on issue status and resolution
 </li>
 <li>
 Maintain high levels of customer satisfaction and service reliability
 
 
 
 </li>
 </ul>
 
 Uptime, Reliability &amp; Operations
 
 
 
 <ul>
 <li>
 Ensure high availability and uptime of customer AI deployments (rack-scale systems)
 </li>
 <li>
 Monitor system health, performance metrics, and workload behavior
 </li>
 <li>
 Implement and manage failover, redundancy, and resiliency mechanisms
 </li>
 <li>
 Proactively identify risks and implement preventative actions
 
 
 
 </li>
 </ul>
 
 AI Inference Workload Support
 
 
 
 <ul>
 <li>
 Support deployment, optimization, and troubleshooting of ML inference pipelines
 </li>
 <li>
 Debug issues across model, runtime, system, and hardware layers
 </li>
 <li>
 Analyze model performance (latency, throughput, accuracy tradeoffs) in production
 </li>
 <li>
 Support frameworks such as PyTorch, TensorFlow, ONNX, and model conversion flows
 </li>
 <li>
 Assist in model optimization techniques (quantization, batching, compilation, runtime tuning)
 
 
 
 </li>
 </ul>
 
 System &amp; Infrastructure Engineering
 
 
 
 <ul>
 <li>
 Support bare-metal and virtualized environments for AI workloads
 </li>
 <li>
 Troubleshoot issues across Linux OS, drivers, firmware, and networking stack
 </li>
 <li>
 Support deployment and maintenance using Infrastructure as Code (IaC) and automation tools
 </li>
 <li>
 Work with DCIM tools and monitoring systems for infrastructure visibility
 </li>
 <li>
 Coordinate with hardware vendors for accelerator, server, and networking issues
 
 
 
 </li>
 </ul>
 
 Monitoring, Observability &amp; Automation
 
 
 
 <ul>
 <li>
 Implement and manage monitoring systems (logs, metrics, traces)
 </li>
 <li>
 Build dashboards for uptime, SLA adherence, performance, and utilization
 </li>
 <li>
 Automate repetitive operational tasks using scripts and workflows
 </li>
 <li>
 Establish and enforce runbooks and standard operating procedures (SOPs)
 
 
 
 </li>
 </ul>
 
 Cross-Functional Collaboration
 
 
 
 <ul>
 <li>
 Work closely with Customer Engineering, Product, Engineering, and Support teams
 </li>
 <li>
 Provide structured feedback to engineering for product improvements and defect resolution
 </li>
 <li>
 Support customer onboarding, deployment readiness, and operational handover
 </li>
 <li>
 Participate in customer reviews, escalations, and technical deep dives
 
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field
 </li>
 <li>
 10&ndash;15+ years of experience in ML operations, systems engineering, or customer support engineering
 </li>
 <li>
 Proven experience in customer-facing technical roles with SLA-driven support models
 </li>
 <li>
 Strong experience with AI/ML inference workloads in production environments
 </li>
 <li>
 Deep understanding of end-to-end ML inference pipelines
 </li>
 <li>
 Hands-on experience with Linux systems, system bring-up, drivers, and debugging tools
 </li>
 <li>
 Strong understanding of AI accelerator architecture and system bottlenecks
 </li>
 <li>
 Experience with model deployment, optimization, and performance tuning
 </li>
 <li>
 Experience with data center operations and rack-scale deployments
 </li>
 <li>
 Familiarity with bare-metal, virtualization, and containerization technologies (Docker, Kubernetes)
 </li>
 <li>
 Knowledge of networking concepts (TCP/IP, RDMA, storage systems)
 </li>
 <li>
 Experience with cloud and hybrid environments
 </li>
 <li>
 Experience with monitoring/observability tools (Prometheus, Grafana, ELK, etc.)
 </li>
 <li>
 Strong skills in incident management, RCA, and production operations
 </li>
 <li>
 Experience defining and tracking SLAs, KPIs, and operational metrics
 </li>
 <li>
 Proficiency in Python, Bash, or similar scripting languages
 </li>
 <li>
 Experience in automation, DevOps, and MLOps tooling
 </li>
 <li>
 Strong problem-solving and diagnostic skills
 </li>
 <li>
 Excellent communication and customer engagement skills
 </li>
 <li>
 Ability to operate in high-pressure, mission-critical environments
 </li>
 <li>
 High attention to detail with a focus on quality, reliability, and accountability
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with Qualcomm Cloud AI or similar AI accelerator platforms
 </li>
 <li>
 Experience supporting large-scale AI deployments (LLMs, CV pipelines, generative AI)
 </li>
 <li>
 Familiarity with inference runtimes (TensorRT, ONNX Runtime, custom runtimes)
 </li>
 <li>
 Experience with CI/CD pipelines for ML deployment
 
 
 
 </li>
 </ul>
 
 Why Join Qualcomm
 
 
 
 At Qualcomm, you&rsquo;ll work at the intersection of
 
 AI silicon, system architecture, and real
 
 ‑
 
 world deployment
 
 . 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
 
 technology direction and customer outcomes
 
 , while working with world‑class engineering and product teams.
 
 
 
 What's On Offer
 
 
 
 Apart from working with great people, we offer the below:
 
 
 <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
 
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <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
 
 
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
 
 
 OR
 
 
 PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
 <ul>
 <li>
 2+ 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.
 
 
 
 </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).
 
 
 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.
 
 
 
 To all Staffing and Recruiting Agencies
 
 : 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.
 
 
 If you would like more information about this role, please contact Qualcomm Careers.
</div>

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

<div>
 
 Company
 
 
 
 Qualcomm Middle East Information Technology Company LLC
 
 
 
 Job Area
 
 
 
 Engineering Group, Engineering Group &gt; Systems Engineering
 
 
 
 General Summary
 
 
 
 
 About Us
 
 
 
 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region
 
 .
 
 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.
 
 
 
 About The Role
 
 
 
 As a Qualcomm Datacenter AI Solutions Engineer, you will research, develop, optimize, and validate software, hardware, architecture, algorithms, and machine learning solutions that enable the deployment of cutting-edge AI datacenter technology.
 
 
 Qualcomm Solution Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. This is a great opportunity to innovate and develop leading-edge products and solutions around best-in-class Qualcomm AI inference accelerators for data center, and hybrid AI applications.
 
 
 
 Principal Duties And Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and optimize AI/ML solutions leveraging Qualcomm AI hardware, software, and ecosystem to deliver high-performance, power‑efficient, and scalable inference
 </li>
 <li>
 Develop and deploy GenAI and LLM-based applications, including model integration, fine-tuning, and optimization
 </li>
 <li>
 Apply systems-level knowledge to analyze, design, implement, and validate AI software, models, and system architecture
 </li>
 <li>
 Perform AI model benchmarking, functional analysis, and performance characterization to drive requirements and improvements
 </li>
 <li>
 Support customer engagements by optimizing AI models and workloads for deployment and inference efficiency
 </li>
 <li>
 Contribute to system-level design efforts, including requirements definition, interfaces, performance targets, and implementation
 </li>
 <li>
 Collaborate closely with cross-functional teams to implement, test, and validate AI system features
 </li>
 <li>
 Debug and triage system-level issues, perform root-cause analysis, and communicate findings clearly
 </li>
 <li>
 Stay current with advancements in AI/ML models, tools, and hardware, and apply innovative ideas to products and solutions
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Master&rsquo;s or PhD in Engineering, Computer Science, Information Systems, or a related field
 </li>
 <li>
 Proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice-based architecture
 </li>
 <li>
 Hands-on experience building, deploying, and tuning AI/ML systems
 </li>
 <li>
 Strong understanding of GenAI architectures (e.g., transformers, diffusion models, LLMs, embeddings)
 </li>
 <li>
 Experience with large-scale AI system design, including distributed systems, fault tolerance, and event-driven architectures
 </li>
 <li>
 Familiarity with MLOps practices and ML lifecycle management
 </li>
 <li>
 Experience with containerization and automation tools (Docker, Kubernetes, Git/GitOps)
 </li>
 <li>
 Experience with model fine-tuning and/or reinforcement learning is a plus
 </li>
 <li>
 Familiarity with observability, benchmarking, and performance analysis for ML pipelines is a plus
 </li>
 <li>
 Experience working in large, matrixed organizations and collaborating across teams
 </li>
 <li>
 Strong problem-solving skills and customer-focused mindset
 </li>
 <li>
 Experience with open-source development practices
 
 
 
 </li>
 </ul>
 
 What's On Offer
 
 
 
 Apart from working with great people, we offer the below:
 
 
 <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
 
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
 
 
 
 </li>
 </ul>
 OR
 
 
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
 
 
 OR
 
 
 PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
 
 
 <ul>
 <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.
 
 
 
 </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).
 
 
 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.
 
 
 
 To all Staffing and Recruiting Agencies
 
 : 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.
 
 
 If you would like more information about this role, please contact Qualcomm Careers.
</div>

Datacenter AI Solutions Engineer (Customer Engagement) – Riyadh, KSA

<div>
 
 
 Company:
 
 
 
 
 Qualcomm Middle East Information Technology Company LLC
 
 
 
 
 Job Area:
 
 
 
 
 Engineering Group, Engineering Group &gt; Software Engineering
 
 
 
 
 General Summary:
 
 
 
 
 
 About Us
 
 
 
 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.
 
 
 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region.
 
 
 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.
 
 
 
 
 About The Role
 
 
 
 
 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.
 
 
 You will bring a strong combination of full-stack engineering expertise, machine learning proficiency, and infrastructure knowledge to build robust, scalable AI systems.
 
 
 
 
 Key Responsibilities Will Include:
 
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 
 Minimum Qualifications
 
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 
 What's On Offer
 
 
 
 
 Apart from working with great people, we offer the below:
 
 
 <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
 
 
 
 </li>
 </ul>
 
 
 Minimum Qualifications:
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
 
 </li>
 </ul>
 OR
 
 
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
 
 
 OR
 
 
 PhD in Engineering, Information Systems, Computer Science, or related field.
 
 
 <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.
 
 
 
 </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).
 
 
 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.
 
 
 
 To all Staffing and Recruiting Agencies
 
 : 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.
 
 
 If you would like more information about this role, please contact Qualcomm Careers.
</div>

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

VaporVM

<div><div>Date Posted: 11 June, 2026
</div><div>Industry: IT Services and IT Consulting
</div><div>Location: VaporVM</div></div>
 <div><h2 class="jobSectionHeader">Job Description:</h2>
<div><h1 class="jobSectionHeader">Senior HPC / Infrastructure Engineer</h1>
Location: Riyadh, Saudi Arabia
Employment Type: Full-Time
Experience: 10+ Years (Hands-On)
<h2 class="jobSectionHeader">Position Overview</h2>
We are seeking a highly experienced Senior HPC / Infrastructure Engineer with proven expertise in designing, deploying, and operating enterprise-scale High-Performance Computing (HPC) and AI infrastructure environments. This role is ideal for a hands-on technical leader who has built and managed production-grade HPC platforms, GPU clusters, Kubernetes ecosystems, and AI infrastructure from the ground up.
The successful candidate will play a critical role in architecting, optimizing, and maintaining mission-critical compute environments that support advanced AI/ML, data science, and high-performance workloads.
<h2 class="jobSectionHeader">Required Certifications</h2>
<ul><li>RHCE &ndash; Red Hat Certified Engineer (Active)</li>
<li>CKA &ndash; Certified Kubernetes Administrator (Active)</li>
</ul><h2 class="jobSectionHeader">Core Technical Expertise</h2>
<h3 class="jobSectionHeader">HPC &amp; NVIDIA AI Ecosystem</h3>
<ul><li>NVIDIA Base Command Manager (BCM)</li>
<li>NVIDIA AI Enterprise</li>
<li>NVIDIA GPU Operator &amp; Network Operator</li>
<li>NVIDIA NIM Inference Services</li>
<li>NVIDIA AI Blueprints</li>
<li>CUDA, GPU Drivers, and Performance Optimization</li>
</ul><h3 class="jobSectionHeader">Compute &amp; Container Platforms</h3>
<ul><li>Kubernetes (Architecture, Operations &amp; Scaling)</li>
<li>Slurm Workload Manager</li>
<li>Distributed Computing Environments</li>
</ul><h3 class="jobSectionHeader">Operating Systems</h3>
<ul><li>Red Hat Enterprise Linux (RHEL)</li>
<li>Ubuntu LTS (Canonical)</li>
</ul><h3 class="jobSectionHeader">Automation &amp; DevOps</h3>
<ul><li>CI/CD Pipeline Design &amp; Implementation</li>
<li>Infrastructure Automation</li>
<li>Platform Lifecycle Management</li>
<li>Configuration Management &amp; Orchestration</li>
</ul><h2 class="jobSectionHeader">Key Responsibilities</h2>
<ul><li>Design, deploy, and operate large-scale HPC and AI infrastructure environments from bare metal through workload orchestration.</li>
<li>Architect and manage NVIDIA GPU platforms, including BCM, AI Enterprise, GPU Operator, and AI service enablement.</li>
<li>Configure, optimize, and maintain Slurm scheduling environments for high-throughput and GPU-intensive workloads.</li>
<li>Design and operate highly available Kubernetes clusters supporting AI/ML, analytics, and containerized workloads.</li>
<li>Enable and support NVIDIA NIM services and AI Blueprint deployments for enterprise AI initiatives.</li>
<li>Administer and optimize RHEL and Ubuntu environments, ensuring stability, security, and performance.</li>
<li>Develop and maintain infrastructure automation frameworks and CI/CD pipelines for platform and application deployment.</li>
<li>Optimize performance across compute, GPU, storage, networking, and cluster resources.</li>
<li>Implement monitoring, observability, alerting, capacity planning, and operational best practices.</li>
<li>Enforce security, patch management, access controls, and compliance standards across the infrastructure stack.</li>
<li>Lead troubleshooting, root cause analysis, and resolution of complex infrastructure and platform issues.</li>
</ul><h2 class="jobSectionHeader">Candidate Profile</h2>
<ul><li>10+ years of hands-on experience in HPC, Linux infrastructure, and enterprise platform engineering.</li>
<li>Proven track record of building and operating production-scale HPC, GPU, or AI infrastructure environments.</li>
<li>Deep expertise in Kubernetes, Slurm, Linux administration, and NVIDIA AI technologies.</li>
<li>Strong understanding of distributed systems, workload scheduling, cluster management, and performance optimization.</li>
<li>Experience supporting AI/ML, data science, and high-performance computing workloads at scale.</li>
<li>Strong analytical, troubleshooting, and problem-solving skills.</li>
<li>Ability to work across infrastructure, platform, automation, and AI enablement domains.</li>
<li>Demonstrated ownership mindset with a history of delivering reliable, scalable, and high-performing solutions.</li></ul></div></div>

Senior Infrastructure / HPC

<div>
 
 Company
 
 
 
 Qualcomm Middle East Information Technology Company LLC
 
 
 
 Job Area
 
 
 
 Engineering Group, Engineering Group &gt; Software Engineering
 
 
 
 General Summary
 
 
 
 About Us
 
 
 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region
 
 .
 
 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.
 
 
 
 About The Role
 
 
 
 We are seeking an Inference Accuracy senior engineer to design, develop, and validate model accuracy of deep learning models deployed at scale. The role focuses on deep accuracy analysis, debugging, accuracy evaluation, and recovery during inference on large data-center hardware platforms. This position requires strong problem-solving ability, excellent Python programming skills, and hands-on expertise with inference pipelines.
 
 
 
 Key Responsibilities Include
 
 
 
 <ul>
 <li>
 Define and implement accuracy KPIs across precision modes
 </li>
 <li>
 Develop scalable Python-based accuracy evaluation tools and automated pipelines.
 </li>
 <li>
 Implement accuracy-preserving optimizations for inference frameworks (TensorRT, ONNX Runtime, AITemplate, Triton).
 </li>
 <li>
 Build and maintain automated pipelines for accuracy evaluation across multiple frameworks (ONNX, TensorFlow, PyTorch).
 </li>
 <li>
 Develop reusable plugins for preprocessing, post-processing, and metric evaluation.
 </li>
 <li>
 Execute comprehensive accuracy tests for large-scale models (LLMs, vision, diffusion).
 </li>
 <li>
 Validate accuracy under various quantization and precision settings (FP32, FP16, INT8).
 </li>
 <li>
 Perform accuracy analysis with deep understanding of model architecture, including layers, attention mechanisms, and parameter configurations.
 </li>
 <li>
 Identify architecture-driven accuracy degradation trends and propose optimization strategies.
 </li>
 <li>
 Identify issues related to preprocessing drift, tokenization mismatches, operator fallback, and quantization effects.
 </li>
 <li>
 Analyze accuracy differences across hardware targets, firmware versions, and runtime backends.
 </li>
 <li>
 Perform slice-based accuracy analysis (batch size, concurrency, sequence length, domain shifts).
 </li>
 <li>
 Design and run experiments to recover accuracy, including fine-tuning, calibration, and hyperparameter adjustments.
 </li>
 <li>
 Debug accuracy failures by tracing root causes across data preprocessing, model layers, quantization steps, and deployment pipelines.
 </li>
 <li>
 Compare results across different hardware/software stacks and generate actionable insights.
 </li>
 <li>
 Document workflows, maintain dashboards, and publish accuracy results for stakeholders.
 
 
 
 </li>
 </ul>
 
 Required Skillset
 
 
 
 <ul>
 <li>
 Strong background in AI/ML model evaluation and accuracy metrics.
 </li>
 <li>
 Solid understanding of model architectures (transformers, CNNs, RNNs, MoE) and their impact on accuracy.
 </li>
 <li>
 Experience with large language models (LLMs) and generative AI accuracy validation.
 </li>
 <li>
 Expertise with inference runtimes (TensorRT, ONNX Runtime, Triton).
 </li>
 <li>
 Understanding of quantization (INT8/FP8/INT4), calibration, QAT, and accuracy trade-offs.
 </li>
 <li>
 Experience with model graph conversion (PyTorch &rarr; ONNX &rarr; backend engines).
 </li>
 <li>
 Hands-on experience with accuracy pipeline development and automation frameworks.
 </li>
 <li>
 Proficiency in Python and familiarity with ML toolkits (ONNX Runtime, TensorFlow, PyTorch).
 </li>
 <li>
 Expertise in accuracy analysis, including statistical methods and visualization tools
 </li>
 <li>
 Ability to design experiments for accuracy recovery and debug accuracy failures effectively.
 </li>
 <li>
 Knowledge of quantization techniques and mixed-precision workflows.
 </li>
 <li>
 Strong problem-solving and analytical skills with the ability to isolate complex accuracy issues.
 
 
 
 </li>
 </ul>
 
 Preferred Skillset
 
 
 
 <ul>
 <li>
 Understanding of video generation model accuracy and multi-modal evaluation benchmarking
 </li>
 <li>
 Experience with data-center accelerators (NVIDIA A100/H100/B200, AI100 Ultra, Gaudi, TPU).
 </li>
 <li>
 Knowledge of LLM accuracy evaluation tools (lm-eval, HELM, synthetic benchmarks) is an advantage
 </li>
 <li>
 Familiarity with distributed deployment systems (Kubernetes, cloud inference services).
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's / Masters degree in Engineering, Machine learning/ AI, Information Systems, Computer Science, or related field.
 </li>
 <li>
 4-10 years of Software Engineering or related work experience.
 </li>
 <li>
 4-10 years of experience with Programming Language such as C,C++, Python.
 
 
 
 </li>
 </ul>
 
 What's On Offer
 
 
 
 Apart from working with great people, we offer the below:
 
 
 <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
 
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <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
 
 
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
 
 
 OR
 
 
 PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
 <ul>
 <li>
 2+ 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.
 
 
 
 </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).
 
 
 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.
 
 
 
 To all Staffing and Recruiting Agencies
 
 : 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.
 
 
 If you would like more information about this role, please contact Qualcomm Careers.
</div>

Model Accuracy Development and Test Engineer, Senior (Datacentre AI Engineering) - Riyadh, KSA

minio

<div><div>MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data.

We&rsquo;re building the complete data stack for AI &mdash; exascale object store, table store, agent memory, and brain: every layer of how AI stores, retrieves, and thinks over data. Hard problems with no existing answers. Bring your own.
<h4 class="jobSectionHeader">
What you will do:</h4>

You&rsquo;ll own problems end-to-end &mdash; the kind most engineering teams never get close to. No ticket queues, no standups, no permission. Just you, the codebase, and a team of people who care as much as you do. Everyone here is an IC, an architect, or a lead &mdash; most are all three.
<h4 class="jobSectionHeader">
Your Skills and Experience:</h4>

Deep OS internals. Networking from the socket layer up. Strong opinions on memory, concurrency, and correctness &mdash; and the humility to revise them. You&rsquo;ve debugged something no one else could reproduce.You&rsquo;ve read source code not because you had to, but because it was bothering you.

Key Competencies:
Fluent in<ul><li> 2 languages, honest about tradeoﬀs</li>
<li>You debug by understanding, not by guessing</li>
<li>Grit: you start hard things and finish them</li>
<li>Curiosity you genuinely can&rsquo;t switch oﬀ</li>
<li>Low ego, extremely high standards</li>
<li>You write code the next engineer respects</li>
<li>Operating Systems, Networking, Systems Programming, Distributed Systems, Storage Engines, Vector/Graph Retrieval, Low -Latency I/O, and Protocol Design</li>
</ul>
MinIO Engineering Culture:
<ul>
<li>All leads, architects and ICs &mdash; no managers</li>
<li>Full ownership from day one, no permission 
needed</li>
<li>Decisions made by the people doing the work</li>
<li>Craftsmanship is a first-class engineering 
concern</li>
<li>No sprints. No standups. No Jira.</li>
</ul><h4 class="jobSectionHeader">What We Offer:</h4>
<ul><li>Health Care Plan (Medical, Dental &amp; Vision)</li>
<li>401K with 3% Contribution</li>
<li>Pre-IPO Stock Options</li>
<li>At least 12 Public Holidays</li>
<li>Flexible Time Off</li>
</ul>
Please include a sample of your work. Examples could include a repo, write up, postmortem, We care more about the work you have done more than a resume. - Submissions without samples will not be considered</div><div><h5 class="jobSectionHeader">
Equal Opportunity Policy (EEO)</h5>

MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.</div></div>

Software Engineer

SiFi

<div>
 
 
 About Us
 
 
 
 
 SiFi is building the next-generation Office of the CFO &mdash; a corporate expense management platform that gives accounting teams seamless control over company spending. We let companies issue cards with precise spending restrictions, automate expense workflows, and close books faster. As we scale, AI is becoming core to how we deliver financial intelligence, automation, and trust to our customers.
 
 
 
 We are a small, high-ownership team. Everyone builds, everyone ships, and everyone is accountable for outcomes.
 
 
 
 
 About the Role
 
 
 
 
 We are looking for an AI Engineer to join our Data &amp; AI team and help us bring AI-powered automation into the heart of corporate finance. You will work across the full stack &mdash; from LLM pipelines and agent workflows to the backend infrastructure and internal tooling that makes them production-ready.
 
 
 
 This is a hands-on, end-to-end role. You will own problems from prototype to production &mdash; in a domain where financial data is structured, high-stakes, and unforgiving. Getting it wrong has real consequences for real companies. You will work closely with Product, Engineering, Finance, and Operations to build AI features that make a direct impact on how hundreds of companies manage money.
 
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design and ship AI-powered features end to end &mdash; from prompt engineering and model integration to backend APIs and frontend surfaces.
 
 </li>
 <li>
 Build and maintain AI infrastructure for LLM inference, retrieval-augmented generation (RAG), and structured data extraction from financial documents
 
 </li>
 <li>
 Develop autonomous agent workflows that automate finance operations such as expense categorization, receipt reconciliation, and policy enforcement
 
 </li>
 <li>
 Partner with the Data Engineering team to ensure AI systems are grounded in clean, trusted, and well-modeled financial data.
 
 </li>
 <li>
 Build internal tooling and evaluation frameworks to measure, monitor, and improve model performance in production.
 
 </li>
 <li>
 Stay close to the state of the art and bring relevant techniques &mdash; fine-tuning, tool use, multi-agent orchestration &mdash; into SiFi's stack where they create real value
 
 
 
 </li>
 </ul>
 Requirements
 
 
 - Strong engineering fundamentals across backend systems, APIs, and cloud infrastructure &mdash; you are comfortable owning the full lifecycle of a production AI feature.
 
 
 - Hands-on experience building with LLMs in production, including prompt design, RAG pipelines, structured extraction, or Agentic systems
 
 
 - Comfort working with financial or compliance-sensitive data, where correctness and audit ability matter
 
 
 - A bias toward shipping &mdash; you move fast, make pragmatic trade offs, and iterate based on real-world feedback
 
 
 - Low ego, high ownership: you are as comfortable debugging an edge case as you are proposing a new system architecture
 
 
 
 
 Nice to Have
 
 
 
 
 - Familiarity with fin-tech or expense management domains
 
 
 - Prior work at an early-stage startup or in a small, high-velocity team
 
 
 
 
 Benefits
 
 
 
 
 Why SiFi
 
 
 
 <ul>
 <li>
 Work on AI problems that are genuinely hard: financial data is structured, high-stakes, and unforgiving &mdash; the opposite of toy problems
 
 </li>
 <li>
 Own meaningful surface area from day one on a lean team where your decisions shape the product.
 
 </li>
 <li>
 Competitive salary and equity
 
 </li>
 <li>
 Flexible working environment
 
 </li>
 <li>
 A front-row seat to building a category-defining fin-tech from the ground up
 
 </li>
 </ul>
</div>

AI Engineer

Explore 189+ Ai inference engineer in Riyadh this July. Find roles across top companies and apply now to boost your career.