Machine Learning Scientist I/II, Scientific Reasoning

Your Impact at LILA As a Machine Learning Scientist focused on Scientific Reasoning, you will help pioneer the next generation of AI systems capable of reasoning like a scientist. You’ll design novel frameworks that push the boundaries of LLM-based reasoning methods — while also implementing scalable frameworks that integrate with Lila’s platforms. This role bridges deep theoretical thinking with practical ML engineering, enabling breakthroughs in how scientific hypotheses are generated, tested, deployed and optimized. What You'll Be Building Design and formalize frameworks for  scientific reasoning with LLMs , including structured prompting, reasoning chains, and test-time compute. Explore and implement methods for  in-context learning, self-reflection, and adaptive reasoning  in scientific discovery workflows. Build  scalable model prototypes that can be deployed to solve frontier scientific problems. Collaborate with scientists and engineers to encode  domain knowledge  into reasoning systems that integrate symbolic and statistical approaches. What You’ll Need to Succeed PhD (preferred) or equivalent research/industry experience in Computer Science, Machine Learning, AI, Engineering, Materials Science or related fields. Strong programming skills in  Python  with deep expertise in LLM frameworks (PyTorch, HuggingFace Transformers, LangChain, LlamaIndex , and related toolkits). Expertise in  LLM reasoning methods : in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning. Ability to balance  theoretical research  with  practical ML engineering  to deliver scalable solutions. Bonus Points For Research experience in  causal reasoning, symbolic AI, or probabilistic programming . Contributions to  open-source LLM reasoning frameworks . Familiarity with  scientific discovery pipelines  in chemistry, biology, or materials science. Experience with  multimodal reasoning  (e.g., combining text, image, and experimental data). Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL). Compensation We offer competitive compensation including bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact. Expected Base Salary Range $176,000 — $304,000 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.