Software Engineer

Responsibilities

• Port and validate key inference and training workloads on new platforms/SKUs
• Build a suite of benchmarks and stress tests to capture end-to-end behavior across CPU, GPU, memory, and networking
• Deep-dive performance on distributed training/inference, including collective performance and tuning
• Create repeatable test harnesses for CI and lab environments
• Partner with systems and fleet bring-up engineers on containerization, K8s integration, and telemetry
• Work cross-functionally with vendors to produce bug reports and prioritized issue lists

Requirements

• BS in CS/EE or equivalent practical experience
• 5+ years in ML systems, performance engineering, distributed systems, or HPC
• Hands-on experience with PyTorch and modern LLM training/inference stacks
• Knowledge of large-scale distributed training concepts (data/model/pipeline parallel)
• Experience with RDMA and debugging/optimizing comms libraries like NCCL or RCCL
• Proficiency in Python and ability to read/write performance-critical code (C++/CUDA/HIP is a plus)
• Strong profiling and debugging skills using tools like Nsight, rocprof, or perf

Preferred Qualifications

• Experience building workload-shaped benchmarks and stress/fault tests
• Familiarity with RDMA networking and transport tuning
• Experience running and validating workloads in Kubernetes
• Hands-on lab experience with early hardware such as new NICs or GPUs

About the Company

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.