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Chaidiscovery

Research Scientist, Pre-training Research

  • Seen live on Chaidiscovery's site today
  • Mid level
Pay
Not stated
Location
San Francisco office
Open for
First seen today
First seen
Nov 4, 2026
Apply on Chaidiscovery's site (opens in a new tab)

Posting record

No flags

First seen today

The posting's record, oldest first
  1. Ghostless first sees this listing
  2. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age.

Last checked Nov 4, 2026.

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

About Chai Discovery

Chai Discovery builds the computer-aided design suite for molecules. Eli Lilly , GSK , Pfizer , Bristol Myers Squibb , argenx and Novartis all use Chai to power drug discovery programs. AI is reinventing life sciences the same way it reinvented software engineering, and our team is building that future.

We train frontier models that learn the underlying foundations of biochemical structure and interaction. We pair this with a computational workspace to iterate on molecules from idea to medicine, helping scientists move faster and develop medicines beyond the reach of existing methods.

We value diverse perspectives and are ready to find greatness in unexpected places.

About the role

We are hiring research scientists to work on foundation model pre-training. Our models learn the foundations of molecular structure and interaction, and their success depends on carefully designed architectural components, training objectives, and data mixes.

At Chai, pre-training research is largely domain-agnostic: understanding model architecture, reading training curves, and knowing when to move between phases of a recipe. We are biased toward simplification, generality, and scale. We adapt the best ideas from frontier language, image, and video models into our domain.

Our models have moved beyond protein structure prediction into real-world therapeutic engineering, and you will have the compute and the team to push that further.

About you

We look for researchers with a strong track record, which can take many forms: getting a model to work, developing impactful theory, or making a substantial contribution to the field. In particular we look for

  • Depth in generative modelling, model architecture, or scaling laws.
  • Hands-on experience designing and training large models.
  • Theoretical grounding in CS, ML, math, or physics.

We are happy to bet on rising talent.

We offer

The opportunity to work at the vanguard of AI research and frontier biology, with world-class people, on a mission that matters. We protect and promote a culture of high velocity and ownership. We compensate our team accordingly.

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