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ML Research Scientist, Scientific Evaluations

Reads like an AI Engineer role: building products on existing AI models.

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

Actively hiring, first seen by us 2 days ago
Pay
USD 176,000–304,000/year · BaseAnnual period assumed — pay source
Expected Base Salary Range $176,000—$304,000 USD About LILA
Read the full posting
Work setting
Not stated
Employment
Not stated

Before you apply

Employer’s visa record
6 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.

What you’ll work on

Full posting
  • 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.

What you’ll bring

All qualifications

Core experience

  • Experience applying ML or computation to biology, chemistry, or materials science
  • Strong track record of creating environments or evaluations for model training
  • Experience building large, complex data pipelines for training or production
  • Strong prototyping and coding skills in Python
  • Solid software engineering fundamentals: clean code, version control, testing
Qualification wording
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.
Solid software engineering fundamentals — clean code, version control, testing, and ability to integrate experimental work into shared infrastructure.

About Lila Sciences

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.

In the employer’s words · Read in context

Apply at Lila Sciences

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 11, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 4 and day 77.

At Lila Sciences, jobs usually come down by about day 65.

From 51 similar postings that came down, and 15 of Lila Sciences’s. Coming down is not always a hire.

Lila Sciences is hiring

19 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • 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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Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

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Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

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.

Job description

View original posting ↗

Your Impact at LILA

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.

Source details

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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.

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