aimlroles

Staff / Principal Research Engineer, AI Safety Mitigations

Lila Sciences Open · verified Oct 22, 2026
Cambridge San Francisco Senior AI Research

At a glance

Senior AI Research role at Lila Sciences. Cambridge · $224,000–$336,000 base.

SalaryStated by Lila Sciences
$224,000 – $336,000
Base salary for this role, in USD per year, as published in the posting.
This role, from Lila SciencesOur estimate for the market: $163,575–$196,250Median $171,000
Above the market median of $171,000 for senior AI research roles in Cambridge.
Worked out from 8 postings that stated pay, median $171,000. Last updated Oct 16, 2026.
RoleAI Research
SenioritySenior
LocationCambridge
Base pay$224,000–$336,000
PostedOct 16, 2026 · 6d ago
Also hiring inSan Francisco
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Turn scientific risk reviews, dual-use policy limits and evaluation results into safeguards with clear, testable requirements
  • Build and test protections such as training changes, classifiers, monitoring, access controls and runtime interventions
  • Measure risk reduction, robustness and effects on legitimate scientific work while tracking practical performance
  • Use adversarial tests, failures and misuse patterns to improve safeguards and investigate regressions or shifts
  • Integrate protections with training, post-training, inference and platform teams across development, release checks and serving

What you bring

  • You have developed and validated safety interventions for frontier models in training, post-training or large-scale inference
  • You bring depth in at least one area, such as safety post-training, classifiers, inference safeguards or platform abuse monitoring
  • You have worked directly with model-development or safeguards teams and the access needed to investigate failures and improve systems
  • You can turn unclear research problems into maintainable implementations and assess robustness, imperfect metrics and trade-offs

Who this fits

This is a senior individual-contributor engineering role for someone who has built safeguards into frontier-model development or deployment. You’ll work across research and engineering teams, with scope spanning research, implementation and integration. The stated U.S. base salary range is $224,000 to $336,000 per year.

From the employer

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to identify and mitigate risks from scientific superintelligence while retaining the core scientific discovery capabilities of the stack. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, safety-focused evaluations, safety systems to mitigate risks, and a research agenda that explores longer-term needs such as oversight of superintelligent scientific systems.

At Lila Sciences, you will develop and test safeguards that reduce societal risks from increasingly capable closed loop scientific AI. This is a high-priority individual contributor role for an engineer who has built safety interventions within the development and deployment of frontier models and wants to apply that experience to scientific models, agents, tools and laboratory-connected workflows.

You will work with domain scientists, risk researchers, evaluators and engineering teams to turn risk findings and policy requirements into effective interventions. The work spans research and implementation: developing approaches, testing their limits and helping integrate reliable safeguards into the systems where they are needed. We are open to different levels of seniority and depth across mitigation approaches.

What You'll Be Building

  • Translate scientific risk assessments, dual-use policy boundaries and evaluation findings into concrete mitigation designs and testable requirements.
  • Develop and implement safeguards suited to the problem, potentially spanning model training, classifiers, monitoring, access controls and runtime interventions.
  • Build experiments that measure risk reduction, robustness and effects on legitimate scientific use, alongside practical performance constraints.
  • Use adversarial findings and observed failures to improve safeguards, working closely with automated-safety and scientific evaluation researchers.
  • Work directly with model-training, post-training, inference and platform teams to integrate mitigations into model development, release evaluation and large-scale serving systems, with appropriate instrumentation and reproducible testing.
  • Investigate regressions, distribution shifts and emerging misuse patterns, and use the evidence to guide further development.

What You'll Need to Succeed

  • Hands-on experience developing and validating safety interventions for frontier models within training, post-training or large-scale inference systems, with contributions to model development or release cycles.
  • Depth in at least one relevant area, such as safety post-training, model-level classifiers, safeguards integrated into inference, or abuse monitoring and enforcement across a model-serving platform.
  • Experience working directly with model-development or safeguards teams, using access appropriate to the intervention—such as training pipelines, model internals, inference infrastructure or systematic evaluation access—to investigate failures and implement improvements.
  • Strong research-engineering skills and the ability to move from an ambiguous problem to working, maintainable implementations.
  • Sound experimental judgment, including an ability to assess robustness, interpret imperfect metrics and reason about competing objectives.
  • The ability to collaborate across research and engineering teams, explain technical trade-offs and take ownership of complex individual contributions.

Bonus Points For

  • 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-generated evidence and policy requirements to training data, evaluation criteria or operational controls.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range$224,000—$336,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.