Senior / Principal Materials Scientist, AI Safety

Lila Sciences, Inc.; Cambridge, San Francisco (MA, CA); On-site; USD 268,000 - 384,000; Full time

Benefits offered by this job

Bonus potential

Equity

Comprehensive benefits (medical, etc.)

Educational assistance program

Commuter benefits

Job summary

Lila Sciences is seeking a Senior/Principal Materials Scientist for AI Safety to map risk across the materials domain and connect deep materials expertise with dual‑use risk assessment. You will help safeguard advanced AI‑driven science while preserving discovery capabilities, with work across Cambridge, MA; London, UK; and San Francisco, CA.

You’ll identify how material properties and processing influence misuse risk, collaborate with threat modelers and labs, and translate dual‑use judgments

Qualifications

• PhD or equivalent in materials science or closely related discipline.
• Experience assessing dual-use risks in materials contexts.
• Ability to investigate risks beyond own specialization.
• Strong scientific communication and cross‑functional collaboration.
• Judgment on physical possibility and uncertainty.

Responsibilities

• Map misuse risks by linking material properties to harmful applications.
• Assess feasibility, processing complexity, and manufacturing constraints.
• Differentiate established vs plausible future capabilities and update assessments.
• Identify gaps and integrate specialist findings into risk landscape.
• Translate dual‑use judgments into policy boundaries and mitigation needs.
• Collaborate with threat modelers, evaluation researchers, and engineers.

Skills

Materials science expertise

Dual-use risk assessment

Scientific communication

Cross-disciplinary collaboration

Analytical judgment

Education

PhD in materials science or related field

Tools

Computational materials science

Automated synthesis & characterization

Job description

Senior / Principal Materials Scientist, AI Safety

Cambridge, MA USA; London, UK; San Francisco, CA USA

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.

We are seeking a materials scientist to map risk across the material sciences domain: you will connect deep materials expertise with dual-use risk assessment to help safeguard increasingly capable scientific AI. You will investigate how advances in materials research could change harmful capabilities, including established and emerging threats.

What You’ll Be Building

• Map misuse risks by connecting material properties, processing and functional performance (across a range of materials domains) to harmful applications, including emerging or overlooked uses of scientific advances.
• Assess how physical feasibility, processing complexity, manufacturing requirements and actors’ resources affect the plausibility and likelihood of misuse, including which constraints AI could change.
• Distinguish established capabilities, plausible future developments and weakly supported hypotheses, revising assessments as evidence changes across models, tools and automated laboratories.
• Identify gaps in expertise, commission targeted scientific input with the expert-program team, and integrate specialist findings into a coherent assessment of the risk landscape.
• Translate dual-use judgments into policy boundaries, evaluation priorities and mitigation requirements that support beneficial materials research.
• Work with threat modelers, evaluation researchers and engineering and experimental colleagues to assess capabilities, interpret red‑team findings and evaluate safeguards.

What You’ll Need to Succeed

• Deep expertise (a PhD, or comparable experience) in materials science or a closely related discipline, with a strong grasp of the relationships between structure, properties, processing and applications. Relevant backgrounds include particulate, porous and formulated systems; and structural and functional materials, including thin films, electrochemical materials and metals and alloys.
• Substantive experience assessing dual-use risks in a relevant area, with a strong understanding of harmful applications such as nuclear proliferation, radiological misuse, weapons‑related capabilities (e.g. energetics) or other consequential materials risks.
• Sound judgment about physical possibility, practical feasibility and uncertainty, together with the ability to investigate risks beyond your immediate specialism.
• The ability to identify appropriate specialists, evaluate technical evidence and synthesize contributions across scientific and security disciplines.
• Clear scientific communication, independent research judgment and an ability to collaborate across science, engineering and policy.

Bonus Points For

• Prior experience applying materials or related physical‑science expertise to AI safety through one or more of: threat analysis, evaluations or red teaming, or mitigation design.
• Experience commissioning specialist research or assessing emerging technologies across disciplinary boundaries.
• Experience with computational materials science, advanced manufacturing or automated synthesis and characterization.

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

$268,000 - $384,000 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.

Lila Sciences iscommitted to equal employment opportunityregardless 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 Sciences' 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.

By submitting this application, you acknowledge that Lila Sciences will process your personal data for recruitment purposes. We’ll retain your information for at least 12 months after the conclusion of the hiring process. For details on your rights and how we handle your data, see our Candidate Privacy Policy at lila.ai/candidate-privacy-policy-notice .