Frontier ML Engineer - Interpretability Platform, Equity

Goodfire; San Francisco (CA); On-site; USD 200,000 - 400,000; Full time

Benefits offered by this job

Market competitive salary

Equity

Competitive benefits

Job summary

An AI interpretability research company in San Francisco is seeking a Machine Learning Engineer to develop tools for interpretable AI systems. The role involves optimizing ML pipelines, implementing research into production, and ensuring system reliability. Candidates should have over 5 years of experience in ML infrastructure, with expertise in Python and distributed systems. This position offers a competitive salary and benefits, along with the chance to contribute to a crucial mission in AI development.

Qualifications

• 5+ years of experience in ML infra, research engineering, or systems programming.
• Expertise in Python, PyTorch or Jax, and distributed systems.
• Experience deploying and maintaining ML systems at scale.

Responsibilities

• Turn cutting edge interpretability research into production ready tools.
• Optimize pipelines and infrastructure for frontier model interpretability.
• Integrate new machine learning workflows into the product.

Skills

ML infra experience

Research engineering

Python

PyTorch

Jax

Distributed systems

Job description

An AI interpretability research company in San Francisco is seeking a Machine Learning Engineer to develop tools for interpretable AI systems. The role involves optimizing ML pipelines, implementing research into production, and ensuring system reliability. Candidates should have over 5 years of experience in ML infrastructure, with expertise in Python and distributed systems. This position offers a competitive salary and benefits, along with the chance to contribute to a crucial mission in AI development.