Senior / Principal Machine Learning Scientist, Scientific Reasoning Models, AI for Drug Discovery

Technical Leadership & Strategy

Lead the design and evolution of scientific reasoning systems, setting technical direction for model architectures, training strategies, and evaluation methodologies.

Model Capability & Improvement

Define and execute approaches to systematically improve model performance on scientific tasks, including long-horizon reasoning and complex decision-making.

Domain Translation

Translate biological and chemical domain knowledge into machine learning objectives, training signals, and evaluation criteria, working closely with domain experts.

Scalable Systems & Engineering

Architect and improve large-scale distributed machine learning systems, ensuring robustness, efficiency, and reproducibility across training and evaluation workflows.

Research-to-Production Impact

Partner with researchers and cross-functional teams to move models from research prototypes to production-ready systems that support active discovery programs.

Who You Are

• PhD in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Experience: For Senior (SE6): 0 – 2+ years of industry or post-doc experience with a focus on deep learning.
• For Principal (SE7): 5+ years of industry or post-PhD experience with a demonstrated track record of technical leadership and project ownership.
• LLM Expertise: Extensive experience developing and training large-scale machine learning models, including approaches to improve domain understanding, reasoning capabilities, and model alignment.
• Publication Record: A strong history of research excellence at top-tier venues (e.g., NeurIPS, ICLR, ICML).
• Engineering: Strong software engineering skills and experience designing and operating large-scale or high-performance machine learning systems.

Preferred Experience

Preferred Experience with molecular modalities (e.g., protein sequences, chemical graphs, and structured molecular data) is highly valued but not required.

Public Portfolio

A public portfolio of research or significant contributions to open-source ML libraries.

Possibly Interested?

• A passion for applying frontier AI to drug discovery.

Qualifications

• The expected salary range for this position, based on the primary location of San Francisco, is $167,400 - 310,800 for the Senior Scientist, and $194,000 - 360,400 for the Principal Scientist.
• The expected salary range for this position, based on the primary location of New York City, is $160,100 - 297,300 for the Senior Scientist, and $185,600 - 344,600 for the Principal Scientist.

Benefits

This position also qualifies for the benefits detailed at the link provided below.

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