Performance Engineer, GPU
About the role
Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency.
You'll work at the intersection of hardware and software, implementing state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization.
Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers.
Requirements
- Have deep experience with GPU programming and optimization at scale
- Be impact-driven, passionate about delivering measurable performance breakthroughs
- Navigate complex systems from hardware interfaces to high-level ML frameworks
- Enjoy collaborative problem-solving and pair programming
- Want to work on state-of-the-art language models with real-world impact
- Care about the societal impacts of your work
- Thrive in ambiguous environments where you define the path forward
Qualifications
- Strong technical background in computer science, electrical engineering, or a related field
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Experience with GPU programming and optimization
- Experience with ML compilers and frameworks
- Experience with performance engineering
- Experience with distributed systems
- Experience with low-precision techniques
- Experience with production systems
Skills
- GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization
- ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators
- Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight
- Distributed Systems: NCCL, NVLink, collective communication, model parallelism
- Low-Precision: INT8/FP8 quantization, mixed-precision techniques
- Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration
Benefits
The annual compensation range for this role is listed below.
- Annual Salary: $280,000 - $850,000 USD
Pay
The annual compensation range for this role is listed below.
- Annual Salary: $280,000 - $850,000 USD
Schedule
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.