Senior Machine Learning Scientist sf, ca

ESRhealthcare • San Francisco, CA

17h • $200,000 - $275,000 • Onsite

About The Position

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. We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery. Qualifications - Essential 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. Qualifications - Nice to have 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)

Requirements

• 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.

Nice To Haves

• 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)

Responsibilities

• Develop and apply machine learning techniques towards building multimodal foundation models that bridge the chemical and biological domains, i.e.: integrate models of chemical structure, target protein sequence and whole transcriptome scRNAseq.
• Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to our problems and datasets.
• Collaborate with our team of biologists and engineers in cross-functional pods to test novel ML-driven hypotheses.

Benefits

• Unlimited Paid Time Off (PTO).
• Monthly Lunch budget.
• One-time Office set up budget.
• US Employees: HMO Kaiser Platinum and PPO Anthem Gold medical as well as vision and dental plans for both the employee and dependents.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree