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Engineering Manager, Distillation & Detection Platform

OpenAI

Engineering Manager, Distillation & Detection Platform is a still-open role at OpenAI on Jobrow. Location: On-site · San Francisco · California · United States. Listed pay: $400k–$445k. Sourced from the company's public Ashby board. First seen 2 months ago; last confirmed 9 days ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
$400k–$445k
Workplace
On-site
Location
San Francisco · California · United States
First seen
2 months ago
Last seen
9 days ago
Board
Ashby
Apply

About this role

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur.

  • Function: Machine learning
  • Seniority: manager

Location & pay

On-site · San Francisco · California · United States Listed pay on Jobrow: $400k–$445k.

Source

Jobrow reads the public Ashby board for OpenAI. First seen 2 months ago; last seen 9 days ago. We are not the employer — apply only on the company ATS.

Posting

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: - Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. - Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. - Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. - Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. - Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. - Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. - Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: - Experience building systems in adversarial, fast-evolving environments - Are comfortable with ambiguity and novelty - Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) - Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. - Significant experience leading engineering teams and delivering production systems end-to-end. - Strong technical judgment in system design, distributed systems, data pipelines, observability, and operational reliability. - Demonstrated ability to partner cross-functionally with Research/Product/Security to ship systems that materially reduce risk or abuse at scale. - Familiarity with model extraction / distillation, adversarial evaluation, or scalable detect

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