Member of Technical Staff, Performance Optimization

📋 Description

• Own performance optimization from GPU kernels to multi-GPU systems.
• Improve latency, throughput, memory, and compute efficiency.
• Profile performance to detect GPU/kernel bottlenecks.
• Implement low-level optimizations using CUDA, Triton, and tools.
• Scale inference and training across multi-GPU, multi-node environments.
• Collaborate with ML researchers to tune models for hardware efficiency.

🎯 Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
• 5+ years of experience in performance optimization or high-performance computing systems.
• Proficiency in CUDA or ROCm and GPU profiling tools (e.g., Nsight, nvprof, CUPTI).
• Familiarity with PyTorch and performance-critical model execution.
• Experience with distributed system debugging and optimization in multi-GPU environments.
• Deep understanding of GPU architecture, parallel programming models, and compute kernels.

🎁 Benefits

• Meaningful equity in a fast-growing startup.
• Comprehensive benefits package.
• Opportunity to work with bleeding-edge AI infrastructure.
• Ownership and impact in a fast-paced, results-driven environment.
• Learn from world-class engineers and researchers.