Hiring.Camp

Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings

Lilasciences

·

Feb 3, 2026

Salary
$176k – $304k
Location
Cambridge, MA USA
Department
Physical Sciences AI
Source
Greenhouse

Description

Your Impact at Lila

We’re hiring a Machine Learning Scientist to advance multi‑modal reasoning with vision‑language models (VLMs) on real-world scientific data including, but not limited to: figures and plots, microscopy data from diverse sources. You’ll design and build state‑of‑the‑art methods to advance the state of Scientific Superintelligence.

What You'll Be Building

  • Lead research on multi‑modal reasoning systems that interpret scientific data (images, plots, text, etc) using state‑of‑the‑art and custom VLMs.
  • Design training, adaptation and test-time methods and strategies (e.g., instruction tuning, supervised learning, RLHF, RAG) for scientific understanding tasks.
  • Build datasets and benchmarks from real scientific artifacts (e.g., microscopy, spectra, protocols) to understand model performance.
  • Develop perception modules (e.g, OCR, table/structure recognition, plot parsing) for multi-modal data modalities.
  • Collaborate with domain scientists and engineers to scale research into production ready systems for scientific superintelligence.

What You’ll Need to Succeed

  • Advanced degree in a relevant field (CS/AI, Applied Math/Stats, EE) or a physical‑sciences discipline (Materials, Chemistry, Physics) with strong ML focus; or equivalent research/industry experience.
  • Track record in multi‑modal ML or VLMs demonstrated via shipped systems, publications, or open‑source.
  • Understanding of scientific QA/benchmarks and custom evaluation design.
  • Experience with multi-modal fine-tuning, document parsing & understanding, dataset curation and benchmarking.
  • Strong engineering skills centered on modern machine learning frameworks (e.g., PyTorch, Huggingface).
  • Clear communication and collaboration in cross‑functional settings.

Bonus Points For

  • Experience with scientific data modalities in real-world laboratories such as microscopy images.
  • Publications in top ML/CV/NLP venues or tangible impact in applied industrial research.
  • Contributions to open‑source multi‑modal tooling, evaluation suites, or datasets.

About Lila

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.

Compensation

We expect the base salary for this role to fall between $176,000- $304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.

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.

Skills

Machine LearningNLPPyTorch

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