Jobs in South San Francisco, CA

About the role

With Tahoe-100M, we solved one of the fundamental bottlenecks in building a virtual model of the cell: generating massive, perturbation-rich, single-cell datasets that capture real biological causality. With Tahoe-x1 , we removed the second bottleneck: creating a modern platform for rapid iteration on model architectures and designs in a cost-efficient manner and at scale. At Tahoe, we embody a simple philosophy: build in the open, shoot for the moon, and we’re looking for people who want to push the frontier of what’s possible. As a Senior Machine Learning Scientist , you will play a leading role in designing the next generation of foundation models of gene regulatory networks powered by Tahoe’s large scale single-cell datasets such as Tahoe-100M and beyond. This role is well-suited for someone with a strong background in machine learning and statistics, and an interest in applying cutting-edge breakthroughs in ML to meaningful problems in drug discovery.

What you'll bring

• We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery.
• PhD or equivalent practical experience in a technical field.
• A proven track record of developing and applying deep learning methods, including experience with modern architectures such as transformers, state-space models, graph neural networks or diffusion-based generative models.
• Proficiency with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow) and core scientific computing libraries (e.g., NumPy, SciPy, Pandas).
• A genuine enthusiasm for applying cutting-edge ML research to real-world biological problems and a bias towards action.
• Prior experience with ML applied to problems in biology or chemistry.
• Familiarity with multimodal modeling, contrastive learning or self-supervised learning.
• Experience with large scale distributed ML techniques (e.g., FSDP, TP, dMoE, flash attention)

Benefits

Locations