Pay
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$200K–$275K against $166K–$240K, the middle half of what similar US postings state.
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Senior Machine Learning Scientist
South San Francisco
Open 7 months, first seen by us 210 days ago- Pay
USD 200,000–275,000/year — pay source
Salary 200,000 – 275,000 USD per year This position requires on-site presence at our South San Francisco office a minimum of three days per week.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- Work authorization
- Must already have the right to work
We welcome applicants who require visa sponsorship and provide work authorization support for qualified candidates
What you’ll work on
Full postingBuild multimodal foundation models linking chemical structure, protein sequence and scRNAseq
Design next-generation gene regulatory network models on single-cell datasets
Rapidly adopt state-of-the-art ML research to Tahoe's problems and datasets
Test novel ML-driven hypotheses with biologists and engineers in cross-functional pods
From the employer’s posting
Develop and apply machine learning techniques towards building multimodal foundation models that bridge the chemical and biological domains
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
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
Education & alternatives
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.
Benefits in the posting
Full benefits wording- Unlimited Paid Time Off (PTO).
- US Employees: HMO Kaiser Platinum and PPO Anthem Gold medical as well as vision and dental plans for both the employee and dependents.
From the employer’s posting.
About Tahoebio-Ai
Tahoe Therapeutics is a biotechnology company working on building the ground truth for biological superintelligence.
In the employer’s words · Read in context
Posting record
Report an errorOpen 7 monthsWe first saw this posting 210 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 15, 2026210 days ago
- Recorded sightings
- 119
- Last seen by us
- Nov 11, 2026
- Employer says posted
- Nov 17, 2025
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 210
Up longer than most. Similar jobs usually come down between day 8 and day 75.
From 5,207 similar postings that came down. Coming down is not always a hire.
Tahoebio-Ai is hiring
2 open jobs
- No new data jobs since April
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- NumPy
- pandas
- PyTorch
- SciPy
- TensorFlow
Where the posting names them
- 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.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Tahoe Therapeutics
Tahoe Therapeutics is a biotechnology company working on building the ground truth for biological superintelligence. 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.
Salary
200,000 – 275,000 USD per year
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.
Source details
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- Pay
Salary 200,000 – 275,000 USD per year This position requires on-site presence at our South San Francisco office a minimum of three days per week.
- Location & working pattern
South San Francisco
200,000 – 275,000 USD per year 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.
- Work authorization
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.