Back to jobs

Senior Machine Learning Engineer

Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
Not stated
Employment
Not stated

Before you apply

Work authorization
Must already have the right to workWe welcome applicants who require visa sponsorship and provide work authorization support for qualified candidates

What you’ll work on

Full posting
  • Design next-generation foundation models of gene regulatory networks

  • Train AI virtual cell models on massive single-cell datasets

  • Build compute-optimized models like Tahoe-x1 with ML Scientists

From the employer’s posting
designing the next generation of foundation models of gene regulatory networks
rapidly adopt state-of-the-art techniques to train AI virtual cell models on our massive single cell datasets
Work together with ML Scientists to develop the next generation of compute optimized models like Tahoe-x1.

What you’ll bring

All qualifications

Core experience

  • Solid engineering and computer science fundamentals, ideally a CS or math degree
  • Experience building, training and deploying modern neural networks such as Transformers
  • Experience with PyTorch, TensorFlow, Keras or JAX
  • Ability to write hardware-optimized code for distributed training
  • Exceptional engineering skills to iterate quickly on data and training pipelines
Qualification wording
Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience.
Experience in building, testing, training, and deploying modern neural network architectures such as Transformers.
Experience with frameworks like PyTorch, Tensorflow, Keras, JAX
the ability to write hardware optimized code for distributed training
Exceptional engineering skills to iterate quickly on data processing and training pipelines

Benefits in the posting

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

From the employer’s posting.

About Tahoebio-Ai

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.

In the employer’s words · Read in context

Apply at Tahoebio-Ai

Posting record

Report an error

Open 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
Dec 2, 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

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,383 postings in the last year. Stated ranges, not salaries paid.

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
Hiring record

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.

  • Keras
  • PyTorch
  • TensorFlow
Where the posting names them
- Experience in building, testing, training, and deploying modern neural network architectures such as Transformers. - Experience with frameworks like PyTorch, Tensorflow, Keras, JAX and the ability to write hardware optimized code for distributed training Qualifications - Desirable

Your next step

Complete your application on jobs.lever.co. The employer’s form will show what is required.

Applying through Lever

  • No account needed: one form, and Lever reads your resume into the profile recruiters search.

Already applied? Track this application

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.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 617, the most 1,122, and the latest week had 1,122.
August 17Last week

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

View original posting ↗

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 Engineer, 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 - Required

  • Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience.
  • Exceptional engineering skills to iterate quickly on data processing and training pipelines
  • Experience in building, testing, training, and deploying modern neural network architectures such as Transformers. 
  • Experience with frameworks like PyTorch, Tensorflow, Keras, JAX and the ability to write hardware optimized code for distributed training

Qualifications - Desirable

  • Experience with distributed deep learning using frameworks such as HF Accelerate, Deepspeed, Composer, TorchTitan, Megatron etc.
  • Experience with training large neural networks on multiple compute nodes.

Key Responsibilities

  • Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to train AI virtual cell models on our massive single cell datasets.
  • Work together with ML Scientists to develop the next generation of compute optimized models like Tahoe-x1.

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.
Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

South San Francisco

- 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.
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.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.