Performance Engineer (GPU)

• 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
• Working at the intersection of hardware and software, you’ll implement 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
• Co-design attention mechanisms and algorithms for next-generation hardware architectures
• Develop custom kernels for emerging quantization formats and mixed-precision techniques
• Design 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 optimize GPU utilization
• Implement kernel fusion strategies to minimize memory bandwidth bottlenecks
• Create resilient systems for planet-scale distributed training infrastructure
• Profile and eliminate performance bottlenecks in production serving infrastructure
• Partner with hardware vendors to influence future accelerator capabilities and software stacks

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents

• Inclusive fertility benefits via Carrot Fertility

• 22 weeks of paid parental leave

• Flexible paid time off and absence policies

• Mental health support for you and your dependents

• Competitive salary and equity packages

• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant

• Retirement plans with competitive matching

• Life and income protection plans

• $500/month flexible wellness and time saver stipend

• Commuter benefits

• Annual education stipend

• Home office stipends

• Relocation support for those moving for Anthropic

• Daily meals and snacks in the office

• 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

• Have deep experience with GPU programming and optimization at scale

• Care about the societal impacts of your work

• Can navigate complex systems from hardware interfaces to high-level ML frameworks

• Are impact-driven, passionate about delivering measurable performance breakthroughs

• Enjoy collaborative problem-solving and pair programming

• Thrive in ambiguous environments where you define the path forward

• Want to work on state-of-the-art language models with real-world impact

• Education requirements: We require at least a Bachelor’s degree in a related field or equivalent experience

• 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

• Deadline to apply: None. Applications will be reviewed on a rolling basis