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Job description
Machine Learning Engineer, Safety | Stealth Mode Frontier AI Lab | Bay Area
I'm working with a well-funded, early-stage stealth AI lab building genuinely frontier systems - and they're hiring a Machine Learning Engineer focused on safety.
The mission: make advanced AI systems reliable, controllable, and aligned as their capabilities grow. This is hands-on, unsolved-problem work at the edge of what's possible.
What you'd work on
Evaluation and oversight systems for advanced reasoning and agentic behaviour
Red-teaming and adversarial testing - turning findings into real model and training improvements
Safety-focused post-training, reward modelling, and guardrails
Identifying and mitigating failure modes in complex, multi-step reasoning
You might be a fit if you have
Strong ML engineering skills and hands-on experience with LLMs / foundation models
Work in one or more of: post-training (SFT/RL/RLHF), evals, red-teaming, alignment, or safety infrastructure
A bias toward shipping and owning problems end-to-end in an ambiguous environment
Real interest in the hard problems of frontier AI safety
Details
Bay Area, hybrid
Small, senior, talent-dense team - real ownership from day one
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.