Senior Machine Learning Scientist

Tahoe Therapeutics; South San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Unlimited Paid Time Off (PTO)

Monthly Lunch Budget

One-time Office Setup Budget

Comprehensive Medical, Vision, and Dental Plans

Job summary

A biotechnology company is seeking a Senior Machine Learning Scientist to drive innovative approaches in drug discovery using advanced ML techniques. The successful candidate will develop models utilizing large-scale datasets, collaborate with a team of experts, and contribute significantly to groundbreaking research within the biological domain.

Qualifications

• Proven track record in developing and applying deep learning methods.
• Experience with modern ML architectures like transformers and graph neural networks.
• Enthusiasm for applying ML research to biological problems.

Responsibilities

• Develop ML techniques for building multi-modal foundation models.
• Collaborate with biologists and engineers in testing ML-driven hypotheses.
• Stay updated with state-of-the-art ML and computational biology research.

Skills

Deep Learning Methods

Machine Learning Frameworks

Statistical Analysis

Data Science

Education

PhD or equivalent in technical field

Tools

PyTorch

JAX

TensorFlow

NumPy

SciPy

Pandas

Job description

About Tahoe Therapeutics

Tahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery — one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world’s largest in vivo single-cell perturbation atlas — and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response. By combining cutting-edge machine learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster — and bring them to more patients who need them.

Your role

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. 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)

Key Responsibilities

• Develop and apply machine learning techniques towards building multi-modal 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.

This hybrid role does not necessitate daily on-site attendance, but it does require the ability to access our offices in either South San Francisco, CA, or Toronto, ON; we welcome applications from candidates in these regions or those willing to relocate to the Bay Area or the Greater Toronto Area. Please note, we have one role open to two geographical locations.