Member of Technical Staff, Performance Optimization

Highlights

• Push speed and efficiency limits across full-stack AI infrastructure.
• Maximize performance of demanding LLMs, vision-language and video models.
• Scale AI systems to meet real-world production demands at global scale.

What they offer

• Equity

Ideal candidate

Performance-obsessed engineer who loves squeezing speed and efficiency from complex systems. You thrive profiling bottlenecks, collaborating with researchers, and scaling cutting-edge generative models for real production impact.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
• 5+ years of experience working on performance optimization or high-performance computing systems
• Proficiency in CUDA or ROCm and experience with 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