Research Engineer

ABOUT CHAI DISCOVERY
Chai builds the design suite for molecules. We train frontier models that learn the underlying foundations of biochemical structure and interaction, so scientists can move faster and pursue targets that other methods cannot reach.
AI is reinventing life sciences the same way it reinvented software engineering, and Chai is at the forefront of this shift. Leading pharmaceutical companies like Eli Lilly https://endpoints.news/eli-lilly-chai-discovery-sign-ai-software-deal/, Pfizer https://www.forbes.com/sites/amyfeldman/2026/06/04/why-pfizer-and-eli-lilly-are-betting-on-this-13-billion-ai-drug-discovery-startup/, and Novartis https://www.chaidiscovery.com/news/novartis-partnership are adopting our platform to power their drug discovery programs.
We value diverse perspectives and are ready to find greatness in unexpected places.
ABOUT THE ROLE
Research engineers make Chai's ML models performant, fast, and reliable at scale by developing the core ML research framework used to train and evaluate our ML models. As a research engineering at Chai Discovery:
- You will develop our agent-powered auto research framework that improves model training and accelerates model inference.
- You will build the frameworks, datasets, and algorithms used to systematically evaluate the performance of our models.
- You will analyze the failure modes of our ML models and work closely with Research Scientists to execute the applied ML experiments needed to mitigate them.
- You will own the distributed ML training stack, eliminating runtime and reliability bottlenecks across the ML model architecture, layer, and kernel levels.
ABOUT YOU
- 4+ years of industry experience working closely or within AI/ML teams.
- Proficiency in Python and experience with Pytorch or JAX.
- Strong software system design skills.
- At least one of the following areas of professional experience:
- Developing and optimizing ML auto-research frameworks.
- Driving Applied ML projects, with a focus on evaluation and iterative improvement.
- Architecting and optimizing GPU clusters and large scale model training.
- Optimizing ML workloads: parallelism, quantization, CUDA/Triton kernels.
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 & promote a culture of high velocity and ownership. We compensate our team accordingly.

Employment type
FullTime

Work arrangement
No