Pay
Higher than most similar jobs
$254K–$310K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Principal, Machine Learning Scientist
San Mateo, CA, San Mateo, CA
Open 3 months, first seen by us 91 days ago- Pay
$254,000–310,000/yearAnnual period assumed — pay source
Total Rewards The salary estimated for this position is $254,000 - $310,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer. What BigHat Offers:
Read the full posting- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type Full Time
Employment type in the employer’s posting: full_time
From the employer’s posting
What you’ll work on
Full postingDesign and implement generative models of antibody sequence and structure
Develop de novo design methods to generate initial hits for hard targets
Build multi-objective sequence optimization for lab-in-the-loop antibody design
Mentor ML and data science staff and interns
Help set the direction of future ML research
From the employer’s posting
Design and implement the next state-of-the-art generative models of antibody sequence and structure
Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems
Provide leadership, technical guidance, and mentorship to other ML and data science FTEs and interns.
Help set strategy for future ML research
Education & alternatives
Skills Knowledge and Expertise - PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background. - Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 91 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
- Aug 5, 202691 days ago
- Recorded sightings
- 49
- Last seen by us
- Nov 4, 2026
- Reposted
- once since Jun 2, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
Time since we first saw it
Day 91
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,362 similar postings that came down. Coming down is not always a hire.
BigHat Biosciences is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- 25% of open jobs were reposted
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.
- Python
- AWS
- PyTorch
Where the posting names them
- Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry. - Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices. - Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
- Familiarity with the current state-of-the-art in ML-driven protein engineering - Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, and experience training and deploying models on AWS. Total Rewards
Your next step
Complete your application on bighatbiosciences.pinpointhq.com. The employer’s form will show what is required.
Applying through Pinpoint
- Only .pdf and .docx are accepted. Older .doc files are turned away.
Already applied? Track this application
Has BigHat Biosciences posted this job before?
Yes. We’ve followed one other Principal, Machine Learning Scientist job there since June 2026. It came down after 61 days.
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
The role: We are seeking a creative, accomplished Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design.
At BigHat Biosciences our full-stack antibody drug development platform uses ML to drive every stage from discovery to optimization. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom LIMS++ data management and orchestration layer to automatically update and deploy the latest models. This makes the development of complex, next-gen therapeutics ‘trivially parallelizable’, at a pace which only accelerates as we develop better ML tooling.
You’re not interested in just git-cloning the latest NeurIPS pub and swapping out the dataset. Motivated by an enthusiasm for the possibility of addressing unmet patient needs and a curiosity about the underlying biology, you’ll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform. Success will mean not only hands-on methods development, but helping shape the direction for future ML research, and actively participating in the application of our platform to the accelerated design of new therapeutics.
Key Responsibilities
- Design and implement the next state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties, trained on proprietary internal datasets of thousands to millions of antibodies.
- Provide leadership, technical guidance, and mentorship to other ML and data science FTEs and interns.
- Help set strategy for future ML research, driven by a strong high-level understanding of BigHat programs and operations as well as real-world drug development challenges.
- Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
- Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems for validation and deployment in our high-throughput wet lab - at BigHat success is only declared upon synthesis of real antibodies with drug-like properties.
- Maintain an in-depth understanding of the current state-of-the-art in ML-driven protein engineering, both in the literature and at BigHat.
- Share your findings at top-tier conferences and publish in leading scientific journals to advance the field of protein engineering.
- Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
- Collaborate with our engineering team to ensure maximal efficiency in the automated and agentic deployment of our latest models to our therapeutics programs.
- Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in BigHat’s platform, and plan and prioritize ML methods development accordingly.
Skills Knowledge and Expertise
- PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background.
- Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry.
- Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices.
- Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
- Enjoys a fast-paced environment and excels at executing across multiple projects.
- Familiarity with the current state-of-the-art in ML-driven protein engineering
- Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, and experience training and deploying models on AWS.
Total Rewards
The salary estimated for this position is $254,000 - $310,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer.
What BigHat Offers:
What BigHat Offers:
- Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived)
- Dental, and vision coverage through Guardian
- Additional well-being benefits through Nayya, OneMedical, Wagmo, Rula, and more
- 401(k) with company match
- DTO, two weeks of company-wide shutdown, and 12 company holidays
- Paid parental leave
Employment type
Full Time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Total Rewards The salary estimated for this position is $254,000 - $310,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer. What BigHat Offers:
- Location & working pattern
San Mateo, CA, San Mateo, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.