Senior Machine Learning Scientist

Tahoe Therapeutics; Emeryville (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Unlimited Paid Time Off (PTO)

Monthly Lunch budget

One-time Office set up budget

Comprehensive health plans for employees and dependents

Job summary

Tahoe Therapeutics is seeking a Senior Machine Learning Scientist to lead the development of foundation models for gene regulatory networks. You will work with large-scale single-cell datasets and collaborate with multidisciplinary teams to tackle real-world challenges in drug discovery.

The ideal candidate has a PhD or equivalent experience and a strong background in deep learning techniques. The role demands on-site presence in South San Francisco at least three days a week and offers a range of benefits including unlimited PTO and comprehensive health plans.

Qualifications

• PhD or equivalent practical experience in a technical field.
• Proven track record of developing and applying deep learning methods.
• Proficiency with modern ML frameworks and core scientific computing libraries.

Responsibilities

• Develop machine learning techniques for multimodal foundation models.
• Adopt state-of-the-art techniques in ML and computational biology.
• Collaborate with biologists and engineers to test ML-driven hypotheses.

Skills

Deep learning methods

Machine learning frameworks

Statistical analysis

Cross-functional collaboration

Education

PhD or equivalent practical experience

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.

Role Summary

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. 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 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

Location and Work Requirements

This position requires on‑site presence at our South San Francisco office a minimum of three days per week.