# Scientist II / Senior ML Scientist, Data-Efficient Learning for Drug Discovery at Lila Sciences

- Company: Lila Sciences
- What the company does: LILA has created the world's first Operating System for Science powered by Scientific Superintelligence™. Backed by General Catalyst.
- Company website: https://www.lila.ai/
- Type: Startups (AI role)
- Level: Senior
- Location: Cambridge, MA USA; London, UK; San Francisco, CA USA
- Work setup: On-site
- Posted: 2026-08-03
- Apply by: 2026-10-08
- Apply: https://job-boards.greenhouse.io/lilasciences/jobs/4340147009
- Page: https://www.1752.vc/careers/jobs/lila-sciences-scientist-ii-senior-ml-scientist-data-efficient-learning-for-drug/

## About the role

Lila Sciences is seeking a Machine Learning Scientist, Data-Efficient Learning for Drug Discovery to build models and learning strategies for settings where data is scarce, expensive, and intentionally generated. This role is focused on training useful models from low-quantity but high-quality datasets ranging from as few as tens to low thousands of examples, often in tightly focused areas of chemical space, and deciding what data should be acquired next.

## What they're looking for

- PhD or equivalent experience in machine learning, computational chemistry, computational biology, statistics, computer science, bioengineering, or a related field
- Strong experience training ML models in low-data regimes
- Experience with active learning, Bayesian optimization, experimental design, meta-learning, fine-tuning, transfer learning, uncertainty estimation, or related data-efficient learning methods
- Experience building ML models for scientific, molecular, biological, chemical, pharmacological, biochemical, or other high-dimensional experimental datasets
- Experience with multimodal learning or methods that combine heterogeneous data sources
- Ability to reason about data acquisition strategy, not only model fitting

Tags: Physical Sciences AI