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Machine Learning Engineer, Safety

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Machine Learning Engineer, Safety in USA

  • San Francisco, CA

Responsibilities

  • Design, build, and maintain ML models and production infrastructure for safety and abuse-detection systems.
  • Improve the accuracy, coverage, latency, and scalability of detection pipelines across the platform.
  • Partner with Security and Infrastructure Engineering to integrate safety systems into core platform infrastructure.
  • Evaluate and integrate third-party safety tooling and vendor models.
  • Track developments in the ML safety and detection landscape and introduce relevant techniques and infrastructure patterns.
  • Use fal’s GPU cluster for inference and evaluation while deploying new safety capabilities at scale.

Requirements

  • Hands-on experience in trust and safety, content moderation, or abuse/detection systems is required.
  • Strong end-to-end engineering fundamentals, including ownership of ML systems and the infrastructure that serves them in production.
  • Ability to own ambiguous, high-stakes problems with limited precedent.

Benefits

  • Competitive salary and equity.
  • Comprehensive benefits package including US health, dental, and vision insurance.
  • Relocation assistance to San Francisco.
  • Learning and growth opportunities, regular team events, and offsites.
  • In-person work in San Francisco five days per week.

Salary: $180k - $250k/yr

fal

fal is a generative media platform that provides developers with access to the world's best generative image, video, and audio models through a unified API. Trusted by over 2.5 million developers and leading companies, fal offers the fastest inference engine for diffusion models, on-demand server...

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