Performance Engineer, GPU
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA · AI Research & Engineering · listed September 22, 2025
The shape of it
Seniority
Not stated
Where
Hybrid
Stated pay
$280,000 – $850,000 USD
Requirements listed
1
Length
1,012 words
In the posting’s own words
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.
What it asks for · 1
- Have deep experience with GPU programming and optimization at scale
Also a plus
- 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
Tools and skills named
Models & research
- GPU9×
- Machine learning3×
- Inference2×
- CUDA
- JAX
- LLM
- PyTorch
Cloud & infra
- Distributed systems
Frameworks
- Node.js
Words the posting leans on
- gpu8×
- performance8×
- systems8×
- kernel5×
- optimization5×
- distributed4×
- hardware4×
- infrastructure4×
- custom3×
- frameworks3×
- gpu performance3×
- implement3×
- language models3×
- architectures2×
- attention2×
- bottlenecks2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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