Joblaze summary

In the role of Performance Engineer at Anthropic, the individual will focus on identifying and resolving complex systems challenges to enhance the performance of large-scale machine learning algorithms. Key skills include experience with high-performance computing, GPU programming, and a solid understanding of machine learning frameworks. This position is ideal for candidates with a strong software engineering background who are eager to deepen their expertise in machine learning while contributing to impactful AI research. Anthropic emphasizes collaboration and communication, fostering a team environment dedicated to advancing trustworthy AI.

Joblaze insights

Listed about 6 months ago — first seen on Joblaze April 14, 2026. Last confirmed on Anthropic's careers page October 28, 2026.
Salary band is above the typical range for AI/ML roles (median ~$190,000).
Starts above 96% of 91 comparable mid ai/ml roles in United States that list AI/ML we track (median $150,000 across 37 companies). See AI/ML salary trends
AI/ML appears in 52.2% of 471 comparable mid ai/ml roles in United States; Accelerator programming appears in 0.2% of 471 comparable mid ai/ml roles in United States.

Quick facts

Is the Performance Engineer role remote?: It's hybrid — Anthropic expects some on-site time in San Francisco, CA | New York City, NY | Seattle, WA.
What's the salary range?: Anthropic lists $280,000–$850,000 for this role.
Where is the role based?: Anthropic is hiring for this position in San Francisco, CA | New York City, NY | Seattle, WA.
What's the tech stack?: Joblaze extracted these technologies from the posting: AI/ML, Accelerator programming, GPU, Language modeling, ML framework internals, Machine Learning.
Does Anthropic sponsor work visas for this role?: Yes — the posting indicates visa sponsorship is available for the right candidate.
What seniority level is this role?: Anthropic targets mid-level candidates for this position.
Is this full-time or contract?: Full-time for this Performance Engineer role at Anthropic.

From the original posting

About Anthropic

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

Standard company text repeated across Anthropic's postings is omitted here.

Performance Engineer