Performance Engineer

Anthropic; New York (NY); Hybrid; USD 280,000 - 850,000; Full time

Benefits offered by this job

Competitive compensation

Optional equity donation matching

Generous vacation and parental leave

Flexible working hours

Job summary

A technology-focused organization in New York is seeking a Performance Engineer to enhance its large-scale machine learning systems. The role involves identifying and solving systems problems while developing robust solutions. Ideal candidates will have software engineering experience, an interest in machine learning, and a collaborative mindset. As a member of a dedicated team, you will work on innovative projects that shape the future of AI. Competitive compensation and benefits are offered, including flexible working options.

Qualifications

• Experience at supercomputing scale is preferred.
• Strong candidates should have a track record of solving large-scale systems problems.
• Desire to learn more about machine learning research.

Responsibilities

• Identify systems problems in large-scale ML algorithms.
• Develop systems to optimize throughput and robustness.
• Work on projects like low-latency sampling for language models.

Skills

Software engineering experience

Machine learning experience

Results-oriented

Flexibility

Pair programming

Concern for societal impacts

Education

Bachelor's degree in a related field

Tools

GPU/Accelerator programming

ML frameworks

Operating systems internals

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

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

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‑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.