Machine Learning Scientist I​/II, Scientific Reasoning

Cambridge, MA USA

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 forscientific reasoning with LLMs, including structured prompting, reasoning chains, and test-time compute.
• Explore and implement methods forin-context learning, self-reflection, and adaptive reasoningin scientific discovery workflows.
• Buildscalable model prototypes that can be deployed to solve frontier scientific problems.
• Collaborate with scientists and engineers to encodedomain knowledgeinto 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 inPythonwith deep expertise in LLM frameworks (PyTorch,Hugging Face Transformers, Lang Chain, Llama Index, and related toolkits).
• Expertise inLLM reasoning methods: in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning.
• Ability to balancetheoretical researchwithpractical ML engineeringto deliver scalable solutions.

Bonus Points For

• Research experience incausal reasoning, symbolic AI, or probabilistic programming.
• Contributions toopen-source LLM reasoning frameworks.
• Familiarity withscientific discovery pipelinesin chemistry, biology, or materials science.
• Experience withmultimodal reasoning(e.g., combining text, image, and experimental data).
• Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL).

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

$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 a.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 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.

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