Machine Learning Engineer
Goodfire is a San Francisco AI interpretability research company building Silico, an agent and infrastructure for understanding, debugging, monitoring, and controlling AI models.
Funding history
About Goodfire
Goodfire is a public benefit corporation and AI interpretability research lab. Its current product, Silico, turns research questions into inspectable experiments and reports, supporting model analysis, debugging, guardrails, and interpretability research.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will turn interpretability research into production-ready tools, optimize infrastructure for model training and inference, integrate machine learning workflows into the product, and ensure reliable, reproducible, high-performing systems.
Requirements
- 5+ years of experience in ML infrastructure, research engineering, or systems programming
- Comfort working across research and engineering boundaries
- Expertise in Python, PyTorch or Jax, and distributed systems
- Experience deploying and maintaining ML systems at scale
- Understanding of model internals and their use in making AI systems more reliable and useful
Responsibilities
- Turn cutting-edge interpretability research into production-ready tools
- Optimize pipelines and infrastructure for frontier-model interpretability, training, and inference
- Integrate machine learning workflows and pipelines into the product and deploy them to customers
- Ensure system reliability, reproducibility, and performance
Benefits
- Equity
- Competitive benefits
- One company-wide remote week per month
