Performance Engineer (GPU)

Anthropic; York and North Yorkshire; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Comprehensive health insurance

Fertility benefits

22 weeks parental leave

Flexible paid time off

Job summary

Anthropic seeks a GPU Performance Engineer to architect and implement foundational systems powering Claude, driving GPU utilization and optimization at unprecedented scale. You will work at the hardware-software boundary, from custom kernel development to distributed multi-node clusters.

Responsibilities include end-to-end optimization of training and inference pipelines, co-design of attention mechanisms for future architectures, and collaboration with hardware vendors to shape accelerator

Qualifications

• Track record delivering GPU performance improvements in production ML systems.
• Experience optimizing end-to-end training and inference pipelines at scale.
• Strong understanding of modern ML frameworks and low-level GPU hardware.

Responsibilities

• Architect and implement foundational GPU performance systems for Claude.
• Maximize GPU utilization and inference efficiency at scale.
• Develop kernel-level optimizations and distributed architectures across thousands of GPUs.
• Co-design attention mechanisms for next-gen hardware architectures.
• Collaborate with hardware vendors to influence accelerator capabilities.

Skills

GPU performance optimization

Collaborative problem-solving

Hardware-software co-design

Education

Bachelor's degree or equivalent experience

Tools

CUDA

Triton

CUTLASS

Flash Attention

Tensor cores

PyTorch/JAX internals

torch.compile

XLA

NCCL

NVLink

Job description

• 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 engineersHave deep experience with GPU programming and optimization at scaleCare about the societal impacts of your workCan navigate complex systems from hardware interfaces to high-level ML frameworksAre impact-driven, passionate about delivering measurable performance breakthroughsEnjoy collaborative problem-solving and pair programmingThrive in ambiguous environments where you define the path forwardWant to work on state-of-the-art language models with real-world impactEducation requirements: We require at least a Bachelor's degree in a related field or equivalent experienceGPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimizationML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operatorsPerformance Engineering: Kernel fusion, memory bandwidth optimization, profiling with NsightDistributed Systems: NCCL, NVLink, collective communication, model parallelismLow-Precision: INT8/FP8 quantization, mixed-precision techniquesProduction Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration