Performance Engineer

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: Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also. You may be a good fit if you: - Have significant software engineering or machine learning experience, particularly at supercomputing scale - Are results-oriented, with a bias towards flexibility and impact - Pick up slack, even if it goes outside your job description - Enjoy pair programming (we love to pair!) - Want to learn more about machine learning research - Care about the societal impacts of your work Strong candidates may also have experience with: - High performance, large-scale ML systems - GPU/Accelerator programming - ML framework internals - OS internals - Language modeling with transformers Representative projects: - Implement low-latency high-throughput sampling for large language models - Implement GPU kernels to adapt our models to low-precision inference - Write a custom load-balancing algorithm to optimize serving efficiency - Build quantitative models of system performance - Design and implement a fault-tolerant distributed system running with a complex network topology - Debug kernel-level network latency spikes in a containerized environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $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! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest

Strong candidates may have: - Significant software engineering or machine learning experience, particularly at supercomputing scale - Experience with high performance, large-scale ML systems - GPU/Accelerator programming - ML framework internals - OS internals - Language modeling with transformers - Ability to implement low-latency high-throughput sampling for large language models - Experience in writing custom load-balancing algorithms, GPU kernels for low-precision inference, and building fault-tolerant distributed systems - A track record of solving large-scale systems problems and interest in ML research

Identify performance and systems problems in large-scale ML deployments and develop systems to optimize throughput and robustness; contribute to the design and implementation of low-latency, high-throughput components; work on GPU kernel development, model optimization for low-precision inference, and fault-tolerant distributed systems; build quantitative models of system performance and improve serving efficiency; collaborate across teams to advance scalable ML infrastructure