Software Engineer, ML Performance And Scaling

at Anthropic
📍 New York City, United States
📍 San Francisco, United States
📍 Seattle, United States
USD 280,000-315,000 per year
MIDDLE
✅ Hybrid

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Algorithms @ 3 Machine Learning @ 3 Communication @ 3 GPU @ 3

Details

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

  • Identify novel systems problems related to running machine learning (ML) algorithms at scale
  • Develop systems to optimize throughput and robustness of the largest distributed ML systems
  • Build infrastructure powering large-scale pre-training runs
  • Develop and optimize the entire pre-training pipeline for Anthropic's AI models
  • Create unified, reliable infrastructure and frameworks maximizing efficiency across computing architectures
  • Work spans immediate product deployment and long-term research initiatives to enable training at increasingly large scales

Requirements

  • Significant software engineering or machine learning experience, particularly at supercomputing scale
  • Results-oriented with a bias towards flexibility and impact
  • Willingness to take on tasks beyond job description
  • Enjoy pair programming
  • Interest in learning more about machine learning research
  • Care about societal impacts 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

  • At least a Bachelor's degree in a related field or equivalent experience

Benefits

  • Competitive compensation and benefits
  • Optional equity donation matching
  • Generous vacation and parental leave
  • Flexible working hours
  • Collaborative office space
  • Visa sponsorship support with immigration lawyer assistance

Additional Information

  • Hybrid work policy: staff expected in office at least 25% of the time
  • Encourages applications from diverse and underrepresented groups
  • Research focus on large-scale AI systems with significant social and ethical implications
  • Emphasizes collaboration and communication

Deadline to apply: None. Applications reviewed on a rolling basis.