AI Performance Engineer (Competitive & Network Analysis)

About the role

Qualcomm is expanding its footprint in Riyadh and is looking to strengthen its data centre and AI infrastructure capabilities across the region. This opportunity sits within Qualcomm Middle East Information Technology Company LLC in the Engineering Group, under Systems Engineering, and supports the company’s broader investment in cloud AI, deep learning, and inference acceleration. As Saudi Arabia advances its digital transformation under Vision 2030, this role offers the chance to contribute to large-scale computing platforms that support AI, cloud services, and next-generation connectivity.

The position is intended for an AI Performance Engineer working at multiple levels. It covers the full lifecycle of the product, from research and development through to deployment in commercial environments. Success in this role requires strong execution, strategic problem-solving, and clear communication in a highly collaborative setting.

Key responsibilities

• Transform, tune, and deploy models for efficient inference using PyTorch and ONNX.
• Explore advanced GenAI methods, including attention mechanisms and mixture-of-experts models, to uncover new ways to improve performance.
• Evaluate and improve inference performance for LLMs, VLMs, and diffusion models, with an emphasis on throughput and latency targets.
• Adapt emerging AI workloads to both current and future hardware architectures.
• Partner with customers and coordinate with internal compiler, firmware, and platform teams to deliver end-to-end solutions.
• Investigate difficult performance and stability issues and drive them toward root-cause resolution.
• Build engineering systems that provide ongoing visibility into AI workload performance and inform continuous improvement.
• Develop high-level kernels, such as in Triton, with the goal of producing efficient low-level code.

Requirements

• Practical experience building and optimizing language models in PyTorch and ONNX, ideally in production environments.
• Strong grasp of transformer architectures, attention mechanisms, and the trade-offs involved in performance tuning.
• Experience with workload mapping approaches that use sharding or other parallelization methods.
• Excellent Python programming ability.
• Curiosity and initiative in learning the latest inference optimization techniques.
• Solid understanding of computer architecture, ML accelerators, in-memory processing, and distributed systems.
• Strong communication and problem-solving skills, with the ability to work effectively in a fast-moving, team-oriented environment.
• Master’s degree in Computer Science, Machine Learning, Computer Engineering, or Electrical Engineering.
• Bachelor’s, Master’s, or PhD in Engineering, Information Systems, Computer Science, or a related discipline, together with relevant systems engineering experience as outlined in the minimum qualifications.

Preferred skills

• Knowledge of neural network operators and mathematical computation, including linear algebra and math libraries.
• Exposure to machine learning compilers.
• Experience evaluating accuracy convergence and related assessment methods.
• Familiarity with torch.compile or torchDynamo.
• PhD in Computer Science, Computer Engineering, or Machine Learning.

Benefits

• Compensation package that includes housing and transportation allowances.
• Stock grant opportunity through RSUs and performance-based bonus pay.
• 16 weeks of fully paid maternity leave.
• 6 weeks of fully paid paternity leave.
• Employee stock purchase plan.
• Child education allowance.
• Relocation support and immigration assistance where required.
• Life and medical insurance coverage.
• Live+ Well reimbursement for health and recreational membership fees.

Minimum qualifications

• Bachelor’s degree in Engineering, Information Systems, Computer Science, or a related field with 4+ years of relevant systems engineering or similar experience; or
• Master’s degree in Engineering, Information Systems, Computer Science, or a related field with 3+ years of relevant systems engineering or similar experience; or
• PhD in Engineering, Information Systems, Computer Science, or a related field with 2+ years of relevant systems engineering or similar experience.
• The stated years of experience are indicative; candidates with comparable experience and the necessary competencies may also be considered.

Additional information

Applicants with disabilities may request accommodations during the application or hiring process. Qualcomm states that it is committed to an accessible recruitment process and workplace. The company also notes that employees must follow all applicable policies and procedures, including security requirements for protecting confidential and proprietary information where permitted by law.

Qualcomm further states that it does not accept unsolicited resumes or applications from staffing or recruiting agencies, and that unauthorized submissions will be treated as unsolicited. For more information about the role, candidates should contact Qualcomm Careers.