Performance Engineer, GPU

About this role

Anthropic seeks a GPU Performance Engineer to optimize large-scale GPU systems powering Claude and advanced language models. You'll develop custom kernels, distributed architectures, and performance innovations across the full hardware-software stack to maximize efficiency at unprecedented scale.

What you'll do

• Design and implement GPU kernel optimizations using CUDA, Triton, and tensor core techniques
• Architect distributed communication strategies for multi-node GPU clusters
• Optimize end-to-end training and inference pipelines for frontier language models
• Build performance modeling frameworks to predict and improve GPU utilization
• Profile production systems to identify and eliminate performance bottlenecks
• Collaborate with hardware vendors to influence future accelerator capabilities

What they're looking for

• GPU programming and optimization (CUDA, Triton, CUTLASS)
• ML frameworks and compilers (PyTorch, JAX, XLA, torch.compile)
• Distributed systems (NCCL, NVLink, collective communication)
• Kernel fusion and memory bandwidth optimization
• Low-precision quantization (INT8/FP8) and mixed-precision techniques
• Performance profiling tools (Nsight)
• Large-scale system design and cluster orchestration
• Model parallelism and distributed training infrastructure

Benefits

• $280,000–$850,000 annual salary
• Hybrid work policy (minimum 25% office presence)
• Work on state-of-the-art AI systems with real-world impact
• Collaborative environment with world-class researchers and engineers
• Opportunity to influence hardware and software evolution