AI Performance Engineer (Competitive & Network Analysis) - Riyadh, KSA

About us

This Role Involves The Following Activities

• Convert, optimize and deploy models for efficient inference using PyTorch, ONNX.
• Work at the forefront of GenAI by understanding advanced algorithms (e.g. attention mechanisms, MoEs) and numerics to identify new optimization opportunities.
• Performance analysis and optimization of LLM, VLM, and diffusion models for inference. Scale performance for throughput and latency constraints.
• Mapping the next generation AI workloads on top of current and future hardware designs.
• Work closely with customers to drive solutions by collaborating with internal compiler, firmware and platform teams.
• Analyze complex performance or stability issues to work towards final root cause of underlying problems.
• Create engineering solutions to deliver continuous insights into performance of AI workloads guiding the improvements over time.
• Design and implement high-level kernels, e.g. in Triton, with a focus on generating efficient, low-level code.

You Will Demonstrate The Following

• Hands-on experience in building and optimizing language models, notably in PyTorch, ONNX, preferably in production-grade environments.
• Deep understanding of transformer architectures, attention mechanisms and performance trade-offs.
• Experience in workload mapping strategies exhibiting sharding or various parallelisms.
• Strong Python programming skills.
• Proactive learning about the latest inference optimization techniques.
• Understanding of computer architecture, ML accelerators, in-memory processing and distributed systems.
• Strong communication, problem-solving skills and ability to learn and work effectively in a fast-paced and collaborative environment.
• MS in Computer Science, Machine Learning, Computer Engineering or Electrical Engineering.

Bonus Skills

• Background in neural network operators and mathematical operations, including linear algebra and math libraries.
• Understanding of machine learning compilers.
• Experience in converging accuracy and its evaluation methods.
• Knowledge of torch.compile or torchDynamo.
• PhD in Computer Science, Computer Engineering or Machine Learning

What's On Offer

• Apart from working with great people, we offer the below:
• 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

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.

OR

OR

• PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
• 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.
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