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Research Engineer, Safety Evaluation

Meta· Safety Evaluation (Meta Superintelligence Labs)
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Menlo Park, CA$219k - $301kFull-timePosted 4w ago

About the role

Meta seeks a Research Engineer to join the Safety Evaluation team to measure and validate the safety of Meta's frontier AI systems. The role designs evaluations, builds infrastructure, and defines measurement standards to gate launches across multimodal models and the broader AI portfolio.

Responsibilities

  • Set the technical strategy for safety evaluation across multiple model families and modalities, and drive it to execution across teams
  • Design, implement, and validate novel evaluations for safety-critical behaviors — policy adherence, adversarial robustness, agentic risk, jailbreak resistance, and emerging harm categories — including for capabilities with no established benchmark
  • Build and harden the distributed evaluation platform so that hundreds of evals run reliably and continuously against checkpoints throughout large-scale training runs
  • Own the measurement quality bar: signal-to-noise, statistical power, saturation, contamination, and construct validity — and establish when an eval is trustworthy enough to gate a launch
  • Create, curate, and analyze high-quality safety datasets, including adversarial, borderline, multilingual, and long-tail cases; convert real-world incidents and red-team findings into durable, repeatable safety signals
  • Diagnose anomalous eval results mid-training-run, determine whether the cause is a model change or an infrastructure artifact, and communicate a clear answer under time pressure
  • Own the dashboards and reporting that researchers, product partners, and leadership use to monitor safety during training and post-launch
  • Translate evolving global safety policy and regulatory standards into concrete, testable measurement criteria, partnering with Policy, Legal, and Integrity
  • Influence the roadmaps of partner research and product teams; mentor engineers and researchers and raise the evaluation bar across the org
  • Represent Meta's safety evaluation methodology to internal leadership and, where appropriate, to external audiences and the research community

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 3+ years of industry research or research-engineering experience in ML/AI, including hands-on work with LLMs, multimodal models, or NLP
  • Demonstrated experience setting technical direction for a large, ambiguous problem area and driving it to delivery across multiple teams
  • Experience designing and validating evaluations or benchmarks for ML systems, including reasoning about metric reliability and failure modes
  • Experience building production-grade or research infrastructure that must be reliable at scale — distributed systems, data pipelines, or evaluation harnesses
  • Programming experience in Python and hands-on experience with frameworks such as PyTorch
  • Experience communicating complex technical results to non-specialist stakeholders and decision-makers

Skills

Required:Strategy and technical leadershipEvaluation design and validationDistributed systems / evaluation harnessesData curation and analysis

Benefits

  • Benefits information is available through Meta's careers portal.
Last updated Oct 23, 2026. Interested? Apply on the company site.

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