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Researcher, Safety Training

OpenAI· Safety Systems
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San Francisco, London, UK$380k - $500k + equityFull-timePosted 11mo ago

About the role

Researcher role focused on advancing safety training for OpenAI’s models, developing post-training methods and safety evaluations to improve model behavior, reliability, and alignment.

Responsibilities

  • Conduct research on safety post-training methods, including RLHF, RLAIF, DPO, PPO, reward modeling, adversarial training, synthetic data, and scalable oversight
  • Develop and implement model training interventions that make models safer, more reliable, and more aligned with user intent
  • Build evaluations and measurement infrastructure for safety harms, high-stakes reliability failures, policy adherence, jailbreak robustness, multimodal risks, agent behavior, and domain-specific risks
  • Translate ambiguous safety problems into concrete research plans, datasets, training runs, evals, and product-facing improvements
  • Analyze model failures such as hallucination, unsafe tool use, prompt injection, privacy leakage, over-refusal, under-refusal, sycophancy, and deceptive or misleading behavior
  • Partner with domain experts to design safety training approaches for areas like cyber, privacy, youth safety, wellbeing, and other frontier-risk domains
  • Collaborate with research and deployment teams to ensure safety improvements are incorporated into OpenAI’s core model training and product launches

Qualifications

  • Have hands-on experience training, fine-tuning, or post-training language models, multimodal models, or agentic systems
  • Have experience with RL, RLHF, RLAIF, DPO, PPO, reward modeling, preference optimization, instruction tuning, or related post-training methods
  • Care deeply about shaping model behavior in real-world systems, not only publishing research
  • Are excited by open-ended safety problems where the right method, dataset, eval, or training objective may not be obvious at the start
  • Bring strong research judgment and strong engineering ability, including comfort running experiments, analyzing model behavior, and working with large-scale ML systems
  • Have experience in one or more relevant domains: agents, tool use, multimodal models, cyber/security, reliability, uncertainty calibration, factuality, evals, privacy, youth safety, wellbeing, or applied alignment
  • Enjoy collaborating across research, engineering, product, policy, legal, and trust and safety teams
  • Hold a PhD in machine learning, computer science, or a related field, or have equivalent practical research or engineering experience

Skills

Required:Post-training methods for language modelsModel training interventionsEvaluation infrastructureCross-functional collaboration

Benefits

  • Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
  • Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
  • 401(k) retirement plan with employer match
  • Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
  • Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
  • 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time
  • Mental health and wellness support
  • Employer-paid basic life and disability coverage
  • Annual learning and development stipend
  • Daily meals in our offices, and meal delivery credits as eligible
  • Relocation support for eligible employees
  • Additional taxable fringe benefits, such as charitable donation matching and wellness stipends
Last updated Oct 22, 2026. Interested? Apply on the company site.

About OpenAI

ai-infrastructure-and-developmentliquid-ai-recruiting-targetllmsetter-30setter-30-2026-q1speech-to-texttext-to-speechvoice-ai-stack
Company profileWebsite

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