Used Tools & Technologies
Not specified
Required Skills & Competences ?
Go @ 3 Algorithms @ 3 Distributed Systems @ 3 Machine Learning @ 3 GPU @ 3Details
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.
Responsibilities
As a Performance Engineer, you will be responsible for identifying novel systems problems in running machine learning (ML) algorithms at scale, and developing systems that optimize throughput and robustness of the largest distributed systems at Anthropic.
Representative Projects:
- Implement low-latency high-throughput sampling for large language models
- Implement GPU kernels to adapt models to low-precision inference
- Write custom load-balancing algorithms to optimize serving efficiency
- Build quantitative models of system performance
- Design and implement fault-tolerant distributed systems with complex network topologies
- Debug kernel-level network latency spikes in containerized environments
Requirements
- Significant software engineering or machine learning experience, especially at supercomputing scale
- Results-oriented with emphasis on flexibility and impact
- Willingness to go beyond core job description tasks
- Enjoyment of pair programming
- Desire to learn more about machine learning research
- Concern about societal impact of 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
Education requirement: At least a Bachelor's degree in a related field or equivalent experience.
Benefits
Anthropic is a public benefit corporation headquartered in San Francisco. Offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a collaborative office space.
Visa sponsorship is available with reasonable effort and support.
Applications are reviewed on a rolling basis with no application deadline.
We emphasize diversity and encourage applications from individuals who may not meet every qualification but are interested in AI's social and ethical implications.
Work Policy
Location-based hybrid policy with expectation to be in-office at least 25% of the time in one of our offices.