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# Machine Learning Engineer

- **Company:** GOODFIRE, LLC
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $200,000.0
- **Contract:** Permanent contract
- **Skills:** Distributed Systems, Python (Programming Language), Machine Learning, System Programming, Pytorch, Reliability of Systems, Machine Learning Operations
- **Published:** August 31, 2026
- **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-2CD1B7C87CFF468A9B/

## About the Role

* 5+ years of experience in ML infra, 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.
 * You care about understanding how models work internally and using that to make them more reliable and useful in the real world., * Startup or frontier lab experience in fast-moving teams.

## Description

We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable frontier AI systems. You'll play a central role in building our core technology, from training and eval tooling to product features, to achieve our mission of understanding and designing the next generation of AI systems.

Where you might contribute:

 * Interpretability tools - Building the tools and infrastructure to support dissection and design of models at frontier scale.
 * Training infrastructure - Extending and supporting our training infrastructure for large training runs.
 * Product - Turning state of the art interpretability research into robust, usable product features.

We'll work with you to determine the team that best aligns with your strengths., * Turn cutting edge interpretability research into production ready tools.

 * Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.
 * Integrate new machine learning workflows and pipelines into our product and deploy to customers.
 * Ensure system reliability, reproducibility, and performance.


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