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Design and prototype new evals and environments for science
Invent new RL environments from scientific workflows, simulators and real-world tasks
Build end-to-end pipelines that generate validated, versioned synthetic environments
Prototype and validate environment designs through reward shaping and training-loop integration
From the employer’s posting
Design and prototype new evals and environments for science
Invent new types of RL environments — explore creative ways to turn scientific workflows, simulators, and real-world tasks into training signal.
Build end-to-end pipelines for synthetic environment generation — transforming raw assets (papers, codebases, lab protocols) into validated, versioned training environments at scale.
Prototype and validate environment designs — from initial concept through reward shaping, data collection, and integration with the training loop.
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Python
Airflow
Where the posting names them
- Experience building large, complex data pipelines for model training or production.
- Strong prototyping and coding skills — comfortable quickly building and iterating on new ideas in Python.
- Creativity and research intuition — ability to identify promising directions, design experiments, and navigate ambiguity.
- Strong publication track record at conferences such as NeurIPS, ICML, and ICLR.
- Strong Python programming skills, including research and production infrastructure
- Familiarity with distributed compute (Ray, Modal) or LLM inference systems (vLLM, batching strategies).
- Familiarity with distributed compute (Ray, Modal) or LLM inference systems (vLLM, batching strategies).
- Experience with async Python, Pydantic, and workflow orchestration frameworks (Flyte, Airflow).
Compensation
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About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Lila is building a platform where AI and automation co-evolve to accelerate scientific discovery. Our AI Research team is looking to hire a ML Research Scientist to focus on building scientific problems and environments to evaluate frontier LLMs on.
What You'll Be Building
Design and prototype new evals and environments for science — creating high-quality evaluations, identifying environment failures, and patching model capability gaps.
Invent new types of RL environments — explore creative ways to turn scientific workflows, simulators, and real-world tasks into training signal.
Build end-to-end pipelines for synthetic environment generation — transforming raw assets (papers, codebases, lab protocols) into validated, versioned training environments at scale.
Prototype and validate environment designs — from initial concept through reward shaping, data collection, and integration with the training loop.
What You'll Need to Succeed
Experience applying ML or computation to biology, chemistry, or material sciences.
A strong track record of creating environments or evaluations for model training
Experience building large, complex data pipelines for model training or production.
Strong prototyping and coding skills — comfortable quickly building and iterating on new ideas in Python.
Creativity and research intuition — ability to identify promising directions, design experiments, and navigate ambiguity.
Solid software engineering fundamentals — clean code, version control, testing, and ability to integrate experimental work into shared infrastructure.
Bonus Points For
Demonstrated experience training large language models
Strong publication track record at conferences such as NeurIPS, ICML, and ICLR.
Strong Python programming skills, including research and production infrastructure
Familiarity with distributed compute (Ray, Modal) or LLM inference systems (vLLM, batching strategies).
Experience with async Python, Pydantic, and workflow orchestration frameworks (Flyte, Airflow).
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 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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Pay
Expected Base Salary Range
$176,000—$304,000 USD
About LILA
Location & working pattern
Cambridge, MA USA; London, UK; San Francisco, CA USA
Working pattern and location restrictions need checking in the full posting.
Work authorization
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.