Research Scientist

present of AI; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Chai Discovery in San Francisco is seeking researchers to advance models that learn how biochemical molecules are built and how they interact. You will work on pre-training large diffusion models, architecture design, post-training, and achieving better inference performance.

The team blends physics, math, CS, and computational biology, and early-career promise is welcomed. Candidates should have a strong research record or solid industry results, practical engineering skills, and a habit of

Qualifications

• The role seeks researchers who can drive models learning biochemical molecules and their interactions.
• Strong engineering ability to implement and optimize models.
• A solid research record or clear industry results, with broad domain grounding.

Responsibilities

• Develop and push forward large diffusion models for molecules.
• Design architectures, perform post-training work, and optimize inference.
• Collaborate across physics, math, CS, and computational biology teams.

Skills

Research track record

Engineering skills

Interdisciplinary background

Job description

AI & Data · San Francisco office · FullTime

The role is for researchers who can push forward models that learn how biochemical molecules are built and how they interact. The work spans pre-training large diffusion models, designing architectures, post-training, and getting more out of models at inference time. A strong candidate brings a solid research record or clear industry results, practical engineering skill, and the habit of staying with hard problems. The team draws from physics, math, computer science and computational biology, and early career people with strong promise are also considered.

How it fits the AI era

The model work itself is the product here, so AI is the main tool and the main subject of the job. Training and refining large generative models for molecules is a direct example of AI moving into life sciences. What stays human is choosing which questions are worth pursuing, judging whether a result is sound, and working with a small team toward a long research plan.

How it builds AI experience

Someone in this role would gain hands-on experience with large generative models applied to real drug discovery programs, from training through to inference. The company's models are used by major pharma partners, so the research connects to real therapeutic engineering work. To build toward it, a candidate can read widely in diffusion models and structure prediction, reproduce results from published papers, and show original ideas through open code or research write-ups.

Worth showing

• Strong engineering ability
• Published research record
• Biochemistry or physics grounding

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Chai Discovery

Frontier AI foundation models and computer-aided design suite to predict and reprogram biochemical molecules, per the company.