About this opportunity
Anthropic lists this Performance Engineer, GPU opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
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.
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.
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.
You might be a good fit if you
Have deep experience with GPU programming and optimization at scale
Are impact‑driven, passionate about delivering measurable performance breakthroughs
Can 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
Strong candidates may also have experience with
GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization
Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight
Representative projects
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
The expected salary range for this position is $280,000 - $850,000 USD .
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location‑based hybrid policy: 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.
Visa sponsorship: We do sponsor visas. If we make you an offer, we will make every reasonable effort to obtain a visa.
As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.