Staff / Principal Research Engineer, AI Safety Mitigations is a AI Safety Engineer role (full-time). with Lila Sciences. in SAN FRANCISCO, US. Compensation shown: $224K–$336K. Imported listing (source: threadangellabs.com). Apply on the employer's site (threadangellabs.com).
Imported listing (source: threadangellabs.com) · Apply on threadangellabs.com
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Imported job description
Sourced from threadangellabs.com
Lila Sciences is hiring a Staff/Principal Research Engineer to build and validate safety mitigations for frontier scientific AI models. The role spans research and implementation, translating risk assessments and policy boundaries into concrete safeguards across training, post-training, inference, and serving systems. You will work with domain scientists, risk researchers, and engineering teams to reduce societal risks while preserving scientific discovery capabilities.
Responsibilities
Translate scientific risk assessments, dual-use policy boundaries, and evaluation findings into concrete mitigation designs and testable requirements
Develop and implement safeguards spanning model training, classifiers, monitoring, access controls, and runtime interventions
Build experiments measuring risk reduction, robustness, and effects on legitimate scientific use
Use adversarial findings and observed failures to improve safeguards with automated-safety and evaluation researchers
Integrate mitigations into model development, release evaluation, and large-scale serving systems with instrumentation and reproducible testing
Investigate regressions, distribution shifts, and emerging misuse patterns to guide further development
Lila Sciences is a scientific AI company developing Scientific Superintelligence and autonomous AI Science Factories for life sciences, chemistry, materials science, medicine, and energy-related discovery. Its platform combines advanced AI models with autonomous laboratory instruments to design, run, interpret, and iterate on scientific experiments.
Hands-on experience developing and validating safety interventions for frontier models in training, post-training, or large-scale inference systems
Depth in at least one area such as safety post-training, model-level classifiers, inference safeguards, or abuse monitoring
Experience working with model-development or safeguards teams using training pipelines, model internals, inference infrastructure, or evaluation access
Strong research-engineering skills and ability to move from ambiguous problems to maintainable implementations
Sound experimental judgment to assess robustness and interpret imperfect metrics
Ability to collaborate across research and engineering teams and explain technical trade-offs
Nice to Have
Experience with scientific models, scientific software, or laboratory-connected systems
Safety work involving tool-using agents, multi-step workflows, or high-consequence misuse
Experience connecting expert evidence and policy requirements to training data, evaluation criteria, or operational controls
Benefits
medical insurancedental insurancevision insurancelife insurancedisability insuranceflexible time offpaid parental leaveeducational assistancecommuter benefitslunch program