Research Engineer, Safety

About the job

Responsibilities

• Research and build safeguards against prompt injection, unsafe tool use, sensitive-data disclosure, policy violations, and hallucinated commitments.
• Build adversarial evaluations, simulations, red-team datasets, and regression suites informed by production failures.
• Develop and deploy classifiers, judges, reward signals, post-training methods, and runtime safeguards for safer agent behavior.
• Analyze production traces and incidents to identify root causes, test mitigations, and measure their impact.
• Partner with Security, Product, Infrastructure, Legal, and customer-facing teams to translate enterprise requirements into scalable safeguards and rollout practices.

Requirements

• 2+ years of experience in AI/ML engineering, research, or AI safety.
• Hands-on experience evaluating, post-training, or deploying language models or agentic systems.
• Experience with modern post-training techniques such as reinforcement learning, preference optimization, distillation, model routing, and synthetic-data generation.
• Experience with adversarial testing, model red teaming, prompt injection, policy enforcement, privacy, or safe tool use.
• Fluency in Python and modern ML tooling, with strong experimental judgment and engineering depth to ship production systems.
• Comfort owning ambiguous, high-stakes technical problems and making clear risk and product tradeoffs.
• Experience building safeguards for high-stakes or regulated enterprise workflows (preferred).
• Familiarity with human-in-the-loop review, incident response, or responsible rollout frameworks for ML systems (preferred).

Benefits

• Equity
• Medical, Dental, and Vision benefits for you and your family
• Life Insurance and Disability Benefits
• Retirement Plan (e.g., 401K, pension)
• Parental Leave
• Fertility and family building benefits through Carrot
• Monthly stipend to support wellness, lifestyle, and work-life balance
• Daily lunches and snacks in the office