Remote ML Research Engineer Jobs
Remote ML Research Engineer jobs are open across the U.S. at remote-first firms and distributed teams in sectors including AI infrastructure, enterprise software, biotech, and defense. Employers hiring remote ml research engineers right now include Rad AI, Truveta, and Whatnot. Find a role that fits below and apply directly.
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Showing 5 of 11+ Remote ML Research Engineer jobs
Company Description
Join us and make YOUR mark on the World!
Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.
Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.
Job Description
We have an opening for a highly motivated Postdoctoral Researcher to conduct research in computational structural biology to develop methods for predicting protein-protein interactions in host-pathogen systems using deep learning (DL).
Current structure prediction tools such as RoseTTAFold3, AlphaFold3, and ESMFold2 excel at monomeric structure prediction and predicting known protein complexes. However, these tools struggle to identify which proteins interact and which do not. You will work to develop specific models that can discriminate between interacting and non-interacting proteins.
You will be an integral member of an interdisciplinary, cross-institution team working with computational biologists, and experimental biologists. You will leverage computational tools and work to develop new DL-based approaches and tools to predict binary interactions, specificity, and structure. You will also work closely with an existing team of computational biologists to understand current capabilities and jointly develop a vision for development of next generation protein design models and tools. You will present your work regularly and publish your research and findings, which includes occasional travel. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.
Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.
In this position, you will
- Conduct research, and contribute to designing, analyzing, and extending DL-based tools for prediction and optimization of protein interaction specificity.
- Participate in the development of protein sequence and structure computational frameworks and analysis tools.
- Collaborate with external partners (Universities, Industry, other National Laboratories) to advance computational biology simulation efforts.
- Prepare complex and detailed progress reports, written analyses, and verbal briefings to support project needs and deadlines and to present research results to sponsors.
- Independently pursue the development of new and innovative research methods relevant to the needs of Laboratory programs and/or external funding agencies.
- Contribute to proposals and statements of work.
- Publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars, and/or technical meetings.
- Travel as needed to coordinate with research collaborators and to attend external meetings and conferences.
- Perform other duties as assigned.
Qualifications
- PhD in Life Sciences, Computational Biology, or Life-science applied ML, Statistics, Computer Science or Mathematics, or a related technical or scientific field.
- Experience developing and implementing deep learning models and algorithms, extracting embeddings, or fine-tuning models using modern software libraries such as PyTorch, or similar as evidenced through publications or software releases.
- Experience working with protein sequence and structure; knowledge in bioinformatics and protein structure modeling sufficient to communicate effectively with team members.
- Ability to work independently on defined research projects, as well as a member of a team with a diverse set of scientists, engineers, and other technical and administrative staff.
- Programming experience with Python and expertise with UNIX and high-performance computing environments.
- Ability to develop independent research projects as demonstrated through publication of peer-reviewed manuscripts.
- Ability to travel as necessary.
Qualifications We Desire
- Understanding and experience in protein bioinformatics, protein structure prediction, and/or protein function prediction.
- Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows.
- Experience in collaborating with experimental and computational biologists.
Pay Range
$122,028 - $143,328 Annually
This is the lowest to highest salary in good faith we would pay for this role at the time of this posting. Pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
Additional Information
#LI-Hybrid
Position Information
This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory?
- Included in 2026 Best Places to Work by Glassdoor!
- Flexible Benefits Package
- 401(k)
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules (*depending on project needs)
- Our values - visit https://www.llnl.gov/inclusion/our-values
Security Clearance
None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check.
National Defense Authorization Act (NDAA)
The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.
Pre-Employment Drug Test
External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Wireless and Medical Devices
Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.
If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.
How to identify fake job advertisements
Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.
To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf
Equal Employment Opportunity
We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
Reasonable Accommodation
Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request.
California Privacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.
Company Description
Join us and make YOUR mark on the World!
Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.
Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.
Job Description
We have an opening for a highly motivated Postdoctoral Researcher to conduct research in computational structural biology to develop methods for predicting protein-protein interactions in host-pathogen systems using deep learning (DL).
Current structure prediction tools such as RoseTTAFold3, AlphaFold3, and ESMFold2 excel at monomeric structure prediction and predicting known protein complexes. However, these tools struggle to identify which proteins interact and which do not. You will work to develop specific models that can discriminate between interacting and non-interacting proteins.
You will be an integral member of an interdisciplinary, cross-institution team working with computational biologists, and experimental biologists. You will leverage computational tools and work to develop new DL-based approaches and tools to predict binary interactions, specificity, and structure. You will also work closely with an existing team of computational biologists to understand current capabilities and jointly develop a vision for development of next generation protein design models and tools. You will present your work regularly and publish your research and findings, which includes occasional travel. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.
Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.
In this position, you will
- Conduct research, and contribute to designing, analyzing, and extending DL-based tools for prediction and optimization of protein interaction specificity.
- Participate in the development of protein sequence and structure computational frameworks and analysis tools.
- Collaborate with external partners (Universities, Industry, other National Laboratories) to advance computational biology simulation efforts.
- Prepare complex and detailed progress reports, written analyses, and verbal briefings to support project needs and deadlines and to present research results to sponsors.
- Independently pursue the development of new and innovative research methods relevant to the needs of Laboratory programs and/or external funding agencies.
- Contribute to proposals and statements of work.
- Publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars, and/or technical meetings.
- Travel as needed to coordinate with research collaborators and to attend external meetings and conferences.
- Perform other duties as assigned.
Qualifications
- PhD in Life Sciences, Computational Biology, or Life-science applied ML, Statistics, Computer Science or Mathematics, or a related technical or scientific field.
- Experience developing and implementing deep learning models and algorithms, extracting embeddings, or fine-tuning models using modern software libraries such as PyTorch, or similar as evidenced through publications or software releases.
- Experience working with protein sequence and structure; knowledge in bioinformatics and protein structure modeling sufficient to communicate effectively with team members.
- Ability to work independently on defined research projects, as well as a member of a team with a diverse set of scientists, engineers, and other technical and administrative staff.
- Programming experience with Python and expertise with UNIX and high-performance computing environments.
- Ability to develop independent research projects as demonstrated through publication of peer-reviewed manuscripts.
- Ability to travel as necessary.
Qualifications We Desire
- Understanding and experience in protein bioinformatics, protein structure prediction, and/or protein function prediction.
- Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows.
- Experience in collaborating with experimental and computational biologists.
Pay Range
$122,028 - $143,328 Annually
This is the lowest to highest salary in good faith we would pay for this role at the time of this posting. Pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
Additional Information
#LI-Hybrid
Position Information
This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory?
- Included in 2026 Best Places to Work by Glassdoor!
- Flexible Benefits Package
- 401(k)
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules (*depending on project needs)
- Our values - visit https://www.llnl.gov/inclusion/our-values
Security Clearance
None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check.
National Defense Authorization Act (NDAA)
The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.
Pre-Employment Drug Test
External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Wireless and Medical Devices
Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.
If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.
How to identify fake job advertisements
Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.
To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf
Equal Employment Opportunity
We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
Reasonable Accommodation
Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request.
California Privacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.
See All 11 Remote ML Research Engineer Jobs
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Find JobsRemote ML Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Staffing & Recruiting
- Technology & Software
What Employers Look For
The qualifications that appear most often in remote ML research engineer jobs.
- Advanced degree in machine learning, computer science, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or JAX
- Experience designing, training, and evaluating large-scale neural network models
- Publication record or demonstrated original research contributions in ML or AI
- Strong mathematical foundation in statistics, linear algebra, and optimization
- Experience with distributed training, cloud compute platforms, or MLOps tooling
Tips for Your Remote ML Research Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote ml research engineer openings from across the U.S. in one place, so you can find roles that match your background and apply directly without sorting through location-filtered noise. Early applications matter because competitive remote postings move fast.
Show your async research communication style
Remote ml research engineer teams rely on written documentation, shared experiment logs, and async code reviews. Include links to research writeups, Weights and Biases experiment summaries, or detailed pull request descriptions in your application materials to prove you can communicate research progress without synchronous standups.
Build a public portfolio of reproducible work
Remote hiring teams evaluate output, not proximity. Publish reproducible notebooks, model cards, and GitHub repositories that reflect the kinds of research problems you solve. Distributed teams can assess your technical depth and working style directly from your public artifacts before a single interview.
Prepare for distributed team interview formats
Remote ml research engineer interviews frequently include take-home research problems, async paper discussions, and multi-round video calls with teammates across time zones. Practice explaining architectural decisions and experimental tradeoffs clearly in writing, since many remote teams use written design reviews as a core evaluation step.
Remote ML Research Engineer Jobs: Frequently Asked Questions
How do I get a remote ml research engineer job?
Target remote-first AI labs, distributed product teams, and research-oriented tech companies, since these organizations are built for async collaboration and hire ml research engineers without geographic constraints. Remote employers screen heavily for self-direction, clear written communication, and the ability to document experiments and decisions asynchronously. A public portfolio of research work, published models, or open-source contributions gives candidates a concrete edge because remote hiring teams evaluate output over in-person presence.
Which companies hire remote ml research engineers?
Employers currently hiring remote ml research engineers include Rad AI, Truveta, and Whatnot, per current remote listings on Migrate Mate as of September 2026. The mix typically includes remote-first AI labs, distributed enterprise software teams, and research divisions in biotech and defense that operate across multiple time zones.
Can you get a remote ml research engineer job with no experience?
Yes, but remote entry-level ml research engineer roles are harder to land because you must demonstrate independent work habits from day one without an office or in-person mentorship. Companies most likely to hire early-career candidates remotely include startups building ML tooling and academic research spinouts. A strong GitHub portfolio, reproducible research notebooks, and contributions to open-source ML projects can substitute meaningfully for formal work history.
Do you need a degree for remote ml research engineer jobs?
Not always, though most remote ml research engineer postings list a graduate degree in machine learning, computer science, or a related field as preferred. Remote employers weigh published research, demonstrable model-building skills, and hands-on results heavily alongside credentials. Candidates without a traditional degree who can show rigorous independent research, open-source contributions, or applied ML projects regularly compete successfully for these roles.
Which industries hire the most remote ml research engineers?
Most remote ml research engineer openings sit in Biotechnology & Pharmaceuticals, Staffing & Recruiting, and Technology & Software, per current remote listings on Migrate Mate as of September 2026. Those sectors rely on distributed research and engineering teams that make remote ml research engineer roles a structural part of how they build and iterate on models.
See All 11 Remote ML Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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