Goodfire

Goodfire

Machine Learning Engineer

San Francisco, CA & New York, NY

Sponsorship not specified$200k-$400kDetected 149 days ago
PythonMachine LearningPyTorchResearch

About the role

  • We'll work with you to determine the team that best aligns with your strengths.

Responsibilities

  • Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.

Requirements

  • 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.
  • Required experience

Nice to have

  • Open-source ML infra contributions.
  • Startup or frontier lab experience in fast-moving teams.
  • Put mission and team first
  • We trust each other, deeply care about the success of the organization, and choose to put our team above ourselves.
  • Improve constantly
  • We proactively critique ourselves and others in a kind and thoughtful way that translates to practical improvements in the organization.
  • Take ownership and initiative
  • There are no bystanders here.

Skills

  • 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.

Compensation

  • The expected salary range for this position is $200,000 - $400,000 USD

Benefits

  • This role offers market competitive salary, equity, and competitive benefits.
  • Integrate new machine learning workflows and pipelines into our product and deploy to customers.

Company info

  • 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 intentionally designing AIs.
Apply directly at Goodfire →Create a free account for alerts like thisView Goodfire immigration profile

This listing is sourced directly from Goodfire's careers page and normalized into a canonical job model.