Scientist II, Mechanics & Extreme Materials

Your Impact at LILA As a Scientist II, Mechanics & Extreme Materials on the Materials Science team at Lila Sciences, you will be the technical expert driving closed-loop learning for extreme materials. Your domain depth in coatings and metal alloys, durability testing, and microstructural analysis will directly shape the experimental methods and automated workflows that power Lila's autonomous science platform. This role sits at the center of Lila's extreme materials program focused on the predictive design of hard, wear-resistant, and corrosion-resistant coatings for aerospace, defense, and industrial applications. You will define how the platform interrogates the performance of new alloy and coating systems, what data it generates, and how those outputs feed back into the next experimental cycle. You will work alongside experimentalists, systems engineers, and machine learning scientists, providing the mechanical and metallurgical judgement that keeps closed-loop campaigns scientifically rigorous and accelerating toward next-generation coating and extreme material solutions. What You'll Be Building Work with Program Lead to drive the strategy for closed-loop campaigns on anti-wear and anti-corrosion materials. Develop, execute and optimize characterization and testing workflows for extreme environment materials, including coatings and bulk materials. Focus areas include: microstructural, mechanical, and tribological analysis for process-structure-property relationships. Collaborate with experimentalists, systems engineers, and ML scientists to integrate characterization outputs into autonomous closed-loop workflows and ML training datasets. Lead experimental design and analysis to extract key materials properties and performance parameters for ML training. Troubleshoot characterization workflows and instrumentation to sustain high-throughput operational performance. Maintain accurate laboratory records and ensure compliance with safety and regulatory standards. What You'll Need to Succeed PhD in Materials Science, Metallurgy, Mechanical Engineering, or related field with 3+ years post-PhD or industry experience. Proficiency in nanoindentation-based mechanical characterization of thin films and bulk materials, including hardness, wear rate, elastic modulus, tribology, and high-throughput testing protocol development. Solid mechanics foundation and deep expertise in microstructural characterization of metal alloys: SEM, TEM, EBSD. Track record developing anti-wear or anti-corrosion materials with measurable performance outcomes. Strong grounding in physical metallurgy and ceramics science: phase equilibria, transformations, sintering, deformation mechanisms, and degradation in extreme environments. Proven ability to interpret structure-property relationships and translate them into experimental design decisions. Effective scientific communicator with experience collaborating across experimental, engineering, and computational teams. Bonus Points For Experience with high-throughput or autonomous experimental workflows. Proficiency in Python or similar tools for data analysis and workflow automation. Exposure to coating deposition and bulk alloy synthesis techniques. Experience with ML-guided experimental design or active learning frameworks. Familiarity with CALPHAD modeling (Thermo-Calc, Pandat) for alloy or ceramic phase prediction. Background in extreme-environment materials testing (high temperature, high stress, or corrosive). 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 $128,000 — $172,000 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.

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