ML Research Scientist, Foundation Models (Senior / Staff / Principal)

What you'll do

• Lead research projects from conception through implementation, designing models and algorithms and running large-scale experiments.
• Collaborate with engineers and drug discovery experts to apply research to the drug discovery platform.
• Publish and present research, and mentor researchers and engineers.

What they ask for

• Deep learning expertise with a portfolio of novel research in generative or predictive modeling.
• Strong coding skills, including the ability to build, debug, and ship models.
• Independent research ownership and strong communication and collaboration skills.
• Willingness to learn about AI, physics, chemistry, and biology; prior biology or chemistry experience is not required.

Nice to have

• PhD in machine learning, computer science, or other computational sciences, or equivalent research experience demonstrated by a strong publication record.
• Experience with PyTorch, PyTorch Lightning, Ray Distributed Training, PyTorch Geometric, distributed training and inference on GPU clusters, or molecular data and related fields.

Tools

diffusion models, flow matching, RL, LLMs, Pytorch, Pytorch Lightning, Ray Distributed Training, Pytorch Geometric

AI focus

Research and build generative and predictive foundation models for molecular systems, including work on reinforcement learning, model architectures, and pretraining and post-training methods for drug discovery.