Model Accuracy and AI , Senior Staff Engineer KSA

Company

Qualcomm Middle Eastern Information Technology Company LLC

Engineering Group, Systems Engineering

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 s 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.

The Qualcomm AI team is developing hardware and software for Machine Learning solutions spanning the data centre, edge, infrastructure, automotive markets and beyond. We are seeking a Senior Staff Machine Learning Engineer to provide hands‑on technical leadership in the design, optimisation, and deployment of machine learning frameworks and applications on Qualcomm AI platforms. This is an individual contributor role that operates with broad technical scope, high autonomy, and significant cross‑team impact.

The successful candidate will drive complex initiatives end‑to‑end, influence technical direction through expertise and execution, and mentor engineers across the organisation while remaining deeply hands‑on. Job activities span the full product life cycle, from early research and architecture through commercial deployment and sustained optimisation.

• Research, design, develop, enhance, and implement the different components of machine learning frameworks, Graph optimisations for performance and accuracy tailored towards Qualcomm NPUs.
• Analyse software requirements, determine feasibility of design within given constraints, consult with architecture and hardware engineers, and implement software solutions best suited for Qualcomm’s SOCs.
• Analyse and identify system‑level integration issues, interface with the software development, integration and test teams.
• Work on latest GenAI techniques and adapt those for NPUs. Architect new techniques that work best on Qualcomm SOCs and architecture.
• Provide technical leadership and mentorship through design reviews, architectural guidance, and hands‑on collaboration, influencing best practices without direct people‑management responsibility.

• Bachelor’s degree in engineering, Information Systems, Computer Science, or related field.
• 12+ years of Systems Engineering or related work experience.

• Internal working knowledge of machine learning frameworks such as PyTorch and Tensor Flow.
• Experience in model-level optimisation using techniques like Torch Compile.
• Expertise in model architecture, backed by literature rationale and intuition.
• Understanding of broad‑spectrum model architectures across modalities, ML algorithms and techniques.
• Expertise in model training and inference workflows.
• Hands‑on experience in C/C++ and Python development (5+ years).
• Experience with object‑oriented design and software development practices.
• Experience with source‑code and configuration‑management tools;
  Git knowledge is required.

• Willingness to work in a cohesive software development environment, including low‑level implementation (code & test) and interfacing with hardware and simulators.
• Experience in neural network architectures and ML compiler workload synthesis.
• Prior working experience with hardware accelerators and hardware‑software co‑design.
• Experience in profiling software and optimisation.
• Passion to develop leading‑edge deep‑learning frameworks and algorithms for mobile and embedded platforms.
• A research mindset with expertise in software development.

• Salary including housing & transport allowance.
• Stock (RSU’s) and performance‑related bonus.
• 16 weeks fully paid maternity leave.
• 6 weeks fully paid paternity leave.
• Employee stock purchase scheme.
• Child education allowance.
• Relocation and immigration support (if needed).
• Life and medical insurance.
• Live + Well reimbursement for health and recreational membership fees.