Research Engineer
Listed by employer · Checked
Older posting · still listed ·
- Work arrangement
- onsite
- Employment
- FullTime
- Stated compensation
- Not specified
Does the location policy fit?
Choose where you would work from. We’ll compare it with the posting’s stated requirements.
Choose a country to check geographic compatibility. The source requirements are available below.
The employer’s posting date is more than 60 days ago. It remained listed at our last successful check; it may be a long-running or evergreen opening. Confirm availability on the original posting before applying.
Browse jobs posted in the past 60 days →This checks the posting’s stated requirements, not your legal right to work. Confirm details with the employer.
Requirements
1 with evidence8 unclear or unstated- Remote policy
- onsite
“Provider workplace type: onsite”
From employer posting metadata - Employment type
- FullTime
9 fields not stated in this posting
- Employer sponsorship
- Not specified
- Geographic scope
- Not specified
- Degree requirement
- Not specified
- Security clearance
- Not mentioned
- Timezone / hours
- Not specified
- Citizenship requirement
- Not mentioned
- Minimum experience (years)
- Not specified
- Work authorization
- Not specified
- Compensation
- Not specified
These details were not stated in the tracked posting. Confirm with the employer.
Original job description
Reading view uses normalized posting text so exact evidence excerpts can be highlighted.
Show less description
Original formatting and links
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
Make our models performant, fast, and reliable at scale by developing the core frameworks used to train and evaluate our ML models.
Build datasets and algorithms to systematically evaluate and monitor model performance.
Analyze model failure modes, working closely with researchers on experiments to mitigate them.
Own the distributed training stack, removing runtime and reliability bottlenecks across all layers of the stack and architecture—parallelism, quantization, and kernel optimization and whatever else might move the needle.
Own and contribute to our auto research and auto kernels frameworks.
Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering. This is a chance to push the frontier of AI drug design, working alongside a rigorous and craft-obsessed team.
About you
Ideal backgrounds include deep industry experience working with top AI/ML teams on the kinds of problems we describe above—with strong software system design skills, proficiency in Python, and Pytorch or JAX fluency. We look for technical spikes where you have gone deep and demonstrated exceptional impact on real-world problems and systems.
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.
Matched by role category. Review each posting’s requirements before applying.