---
title: 'Senior Machine Learning Scientist at Tahoe Therapeutics'
canonical: 'https://feeny.ai/job/senior-machine-learning-scientist-tahoe-therapeutics-south-san-francisco-31vx0qt1qs41'
type: 'job'
last_seen: '2026-09-12'
---

# Senior Machine Learning Scientist at Tahoe Therapeutics

- **Company:** Tahoe Therapeutics
- **Location:** South San Francisco, CA
- **Compensation:** $200k–$275k
- **Work type:** onsite
- **Posted:** 2025-11-17
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.lever.co/tahoebio-ai/8fe3e406-050f-498c-8f75-3cb780dec092

## 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

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. 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.

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

We welcome applicants who require visa sponsorship and provide work authorization support for qualified candidates.

## About Tahoe Therapeutics

## Company Overview
- **One-liner**: Tahoe Therapeutics builds the ground truth for biological superintelligence by generating large-scale perturbative single-cell data and training AI models to predict cellular responses, transforming drug discovery.
- **Entity Type**: Private (Series A)
- **Headquarters**: South San Francisco, California, USA
- **Founded**: 2022 (formerly Vevo Therapeutics)
- **Founders**: Nima Alidoust (CEO & Cofounder), Johnny Yu (CSO & Cofounder), Hani Goodarzi (Cofounder)

## Core Business
- **Primary industry**: Biotechnology / AI-powered drug discovery
- **Target customers**: Biopharmaceutical companies, research institutions, and drug discovery partners
- **Mission/purpose**: To build the ground truth for biological superintelligence — generating in vivo data at scale and training AI models to discover better drugs for more patients, including targets previously considered "undruggable."

## Products & Services
- **Mosaic Platform**: Proprietary in vivo drug discovery platform that generates perturbative single-cell data at scale and single-cell precision across primary cells, organoids, iPSC-derived cells, and in vivo models with immune context.
- **Rhaister**: A machine learning model for drug response prediction that learns from Tahoe's generated data and creates synthetic data for new biological contexts — trained in seconds, running in milliseconds.
- **Tara**: An autonomous research agent that traverses Tahoe's data ocean, generates hypotheses, validates them, and surfaces discoveries rather than guesses.
- **Tahoe-100M**: The world's largest open-source single-cell dataset, released as the inaugural contribution to Arc Institute's Virtual Cell Atlas.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Total funding of $72M across three rounds (Seed $12M in 2022; two Series A rounds of $30M each in 2025)
- **Notable Investors/Partners**: Wing Venture Capital, General Catalyst, Amplify Partners; partners include Parse Biosciences GigaLab, Arc Institute, and Alloy Therapeutics (joint venture for antibody-drug conjugates)
- **Growth Signals**: Headcount grew ~40% YoY to ~29 employees; active job postings up 400% YoY; published the GENEVA platform in Nature Cancer (2026); released Rhaister (2026); formed ADC joint venture with Alloy Therapeutics (2026); open-sourced Tahoe-100M dataset (2025)

## Competitive Advantages
- **Proprietary data flywheel**: Mosaic generates in vivo single-cell perturbation data at a scale and diversity competitors cannot easily replicate, feeding AI models that improve with each dataset.
- **Open-source leadership**: Tahoe-100M is the largest open single-cell dataset, establishing the company as a standard-setter in the virtual cell atlas space.
- **World-class team**: Founders and leadership have discovered drugs for undruggable targets, trained frontier AI models on chemical/biological data, and invented novel methods in single-cell and cancer biology.
- **Integrated verification loop**: Tara closes the loop between hypothesis generation and validation, reducing reliance on guesses and accelerating discovery.

## Strategic Focus
- Scaling the world's largest in vivo atlas of how drugs interact with patient cells.
- Advancing AI models (Rhaister and successors) for drug response prediction and synthetic data generation.
- Expanding therapeutic partnerships, including the Alloy Therapeutics joint venture for first-in-class antibody-drug conjugates.
- Growing the team across machine learning, research, and drug discovery to support platform development and pipeline advancement.

## Why Work Here
- **Culture**: "We are not content with incrementalism. We make big bets and work hard to make sure they happen." Team is dynamic, mission-driven, and focused on high-impact science.
- **Work model**: Roles are primarily on-site in South San Francisco, with some hybrid opportunities (e.g., drug discovery roles). Current openings include Senior/Staff Full-Stack Engineer, Senior Machine Learning Engineer, Senior Machine Learning Scientist, and Research Associate.
- **Perks & environment**: Inaugural hackathon for building on Tahoe-100M; exposure to cutting-edge AI + biotech; collaboration with top academic and industry partners; strong growth trajectory with a 40% headcount increase and expanding job postings.
- **Caveat**: Employer rating is 2.3/5 based on 9 reviews (culture 2.0, career 2.1, compensation 2.9, work-life 3.5) — a small sample that may not reflect the current evolving environment.

## Sources
1. [tahoebio.ai](https://www.tahoebio.ai/)
2. [tahoebio.ai/about](https://www.tahoebio.ai/about)
3. [jobs.lever.co](https://jobs.lever.co/tahoebio-ai)
4. [linkedin.com](https://linkedin.com/company/tahoe-therapeutics)
5. [cbinsights.com](https://www.cbinsights.com/company/vevo-therapeutics)

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