Software Engineer, Ml Performance And Scaling

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The team includes researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

As a Performance Engineer, you will tackle novel systems problems arising from running machine learning algorithms at scale. Your responsibility includes identifying problems and developing systems to optimize throughput and robustness of large distributed systems. The Scaling Team builds and optimizes infrastructure powering large-scale pre-training runs, working at the intersection of research, performance, and distributed systems. The work includes developing unified, reliable infrastructure maximizing efficiency across different computing architectures, supporting both immediate product deployment and long-term research.

You May Be a Good Fit If You:

• Have significant software engineering or machine learning experience, especially at supercomputing scale
• Are results-oriented with flexibility and impact focus
• Are willing to take on tasks outside of your job description
• Enjoy pair programming
• Want to learn more about machine learning research
• Care about 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:

• Implementing low-latency, high-throughput sampling for large language models
• Developing GPU kernels for low-precision inference
• Creating custom load-balancing algorithms for serving efficiency
• Building quantitative models of system performance
• Designing fault-tolerant distributed systems with complex network topology
• Debugging kernel-level network latency spikes in containerized environments

Logistics

• Education: At least a Bachelor's degree in a related field or equivalent experience
• Location-based Hybrid Policy: Staff are expected to be in office at least 25% of the time
• Visa Sponsorship: Available with reasonable effort and legal support

How We're Different

Anthropic pursues large-scale, high-impact AI research as big science, valuing collaboration and communication. They focus on steerable, trustworthy AI, aligning with empirical science traditions and emphasizing social and ethical AI implications.

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Collaborative office space

Applicants are encouraged to apply even if they do not meet every qualification fully, with a commitment to diversity and inclusion.