Member of Technical Staff Performance Optimization

You will optimize AI workloads across GPU kernels and distributed systems. You will profile bottlenecks, improve latency and resource efficiency, implement CUDA and Triton optimizations, benchmark performance, and scale training and inference across multi-GPU and multi-node environments.

Responsibilities

• Optimize system and GPU performance for AI workloads
• Improve latency, throughput, memory usage, and compute efficiency
• Profile and resolve GPU and kernel bottlenecks
• Implement low-level optimizations with CUDA and Triton
• Improve execution speed and resource utilization
• Co-design hardware-efficient model architectures
• Build performance benchmarking and monitoring infrastructure
• Scale inference and training across multi-GPU and multi-node environments
• Evaluate emerging hardware accelerators and runtimes

Requirements

• Performance optimization
• High-performance computing
• CUDA
• ROCm
• GPU profiling
• Nsight
• nvprof
• CUPTI
• PyTorch
• Distributed system
• GPU architecture
• Parallel programming
• Compute kernel

Benefits

• Equity