Performance Engineer

Anthropic; San Francisco (CA); On-site; USD 280,000 - 850,000; Full time

Job summary

Anthropic is seeking a Performance Engineer to optimize throughput and robustness of our largest distributed systems running at scale. You will identify novel problems, design solutions, and grow into a ML expert while solving challenging systems issues.

The role emphasizes collaboration with researchers, engineers, policy experts, and business leaders to build reliable AI systems that are safe and beneficial for users and society.

Qualifications

• 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.
• Want to learn more about machine learning research.
• Care about the societal impacts of your work.

Responsibilities

• 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.

Skills

Software engineering experience

Machine learning experience

Results-oriented

Pair programming

ML research interest

Societal impact awareness

Flexibility and impact

Education

Bachelor’s degree or equivalent

Tools

GPU/Accelerator programming

ML framework internals

OS internals

Transformers language modeling

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

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.

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 results show 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.

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-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.