ML Research Scientist, Environments & Harnesses

Lila Sciences; Cambridge, San Francisco (MA, CA); On-site; USD 228,000 - 304,000; Full time

Job summary

Lila Sciences in Cambridge, MA is seeking an ML Research Scientist focused on synthetic RL environment pipelines and multi-agent harness design. You will design harness capabilities, invent new RL environments, and build scalable end-to-end pipelines.

Ideal candidates have a PhD, strong Python prototyping, and a track record in RL research, with engagement in experiments and shared infrastructural work.

Qualifications

• PhD or equivalent in CS or related field required.
• 2+ years industry experience preferred.
• Strong Python coding and prototyping skills.
• Solid understanding of RL concepts.
• Ability to design and run experiments.

Responsibilities

• Design and prototype multi-agent harness capabilities.
• Create novel RL environments from scientific workflows.
• Build end-to-end pipelines for synthetic environments.
• Prototype and validate environment designs within training loop.
• Advance multi-step reasoning and evaluation scenarios.

Skills

Python programming

Reinforcement learning

Software engineering basics

Prototyping

Research mindset

Education

PhD or equivalent in CS or related field

Job description

ML Research Scientist, Environments & Harnesses

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

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 synthetic RL environment pipelines and multi-agent harness design. These core pillars enable efficient scaling at training and test time to unlock scientific discovery. Lila’s scale and unique focus on experimental science means solving novel problems and building infrastructure that scales.

What You'll Be Building

• Design and prototype new harness capabilities — context compaction strategies, novel tool interfaces, long-horizon planning mechanisms, mult-agent swarms, and other innovations that expand what agents can do.
• 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.
• Push the boundaries of multi-step reasoning — design and implement support for chained tasks, hierarchical goals, and complex evaluation scenarios.

What You'll Need to Succeed

• PhD (or equivalent experience) in Computer Science or a related quantitative field and two years of industry experience.
• A strong track record ideating on new harness designs or creating reinforcement learning environments at scale.
• 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.
• Familiarity with core concepts and algorithms in reinforcement learning.
• Solid software engineering fundamentals — clean code, version control, testing, and ability to integrate experimental work into shared infrastructure.

Bonus Points for

• Strong publication track record at conferences such as NeurIPS, ICML, and ICLR.
• Background in biology, chemistry, or physics — or experience translating domain expertise into computational tasks.
• Experience building developer-facing libraries, APIs, or frameworks (registries, plugin systems, CLIs).
• 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

$228,000 - $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.

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.

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