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Machine Learning Engineer, Safety
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Job Description
Machine Learning Engineer, Safety at Harrison Clarke Machine Learning Engineer, Safety at Harrison Clarke in Union City, California Posted in 2 days ago.
Type:
full-time 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 Highly competitive compensation