AI ML Performance Engineer

About the Role

We are looking for an experienced AI/ML Performance Engineer to design and execute high-intensity stress workloads for next-generation AI platforms. This role focuses on identifying performance bottlenecks, improving system stability, and enabling scalable, production-ready AI infrastructure.

Key Responsibilities

• Design and implement high-intensity stress workloads using PyTorch and Triton
• Analyze system performance to identify bottlenecks, stability issues, and performance cliffs
• Develop workloads targeting large GEMMs, attention mechanisms, MoE-like architectures, mixed precision, and long-running executions
• Build custom Triton kernels to stress hardware execution units, memory hierarchies, and synchronization paths
• Create scalable test harnesses across problem size, number of devices, and runtime duration
• Integrate workloads with profiling, monitoring, and failure triage tools
• Collaborate with platform, firmware, and SDK teams
• Provide documentation and reproducible scripts for lab and CI environments

Required Skills

• Strong experience in performance testing and analysis (test result analysis, server stats, bottleneck identification, tuning, and recommendations)
• Proficiency in Python
• Scripting experience using Shell or PowerShell
• Experience with PyTorch and/or Triton

Nice to Have

• Experience with AI hardware platforms or simulators
• Exposure to distributed systems and multi-device workloads