2

Remote Bioinformatics Machine Learning Jobs in Boston, MA

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

S. government security clearance in the future.' This is NOT a fully remote position! Required * BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI ...

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Hybrid work with core in-office days and flexible remote options * Leadership and technical ...

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Hybrid work with core in-office days and flexible remote options * Leadership and technical ...

Summary: The Machine Learning Engineer (SMTS) designs and implements machine learning (ML ... bioinformatics, and more. Duties/Responsibilities Designs and develops AI models to meet project ...

Senior Machine Learning Engineer

Boston, MA · Remote

$125K - $165K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

The Opportunity Nucs AI is looking for a Machine Learning Scientist to deepen our ML research ... Autonomy and flexibility - Remote-first, flexible working. We hire great people and trust them to ...

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in ... LI-Remote We value diversity and believe the unique contributions each of us brings drives our ...

Machine Learning Systems Engineer

Boston, MA · On-site +1

$144K - $192K/yr

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

Utilize machine learning and statistical modeling to uncover patterns that inform clinical decision ... D. in Bioinformatics, Computational Biology, Genetics, or a closely related field. ● A minimum of ...

Lead Machine Learning Engineer - REMOTE

Boston, MA · On-site +1

$111K - $146K/yr

Join a Company that Empowers you to Build your Future Lennar is seeking a Machine Learning Engineer ... Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or ...

next page

Showing results 1-20

Remote Bioinformatics Machine Learning information

See Boston, MA salary details

$64.6K

$102.6K

$162.4K

How much do remote bioinformatics machine learning jobs pay per year?

As of Jul 12, 2026, the average yearly pay for remote bioinformatics machine learning in Boston, MA is $102,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,300.00 and $140,700.00 per year, depending on experience, location, and employer.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is a Remote Bioinformatics Machine Learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What are the key skills and qualifications needed to thrive as a Remote Bioinformatics Machine Learning Specialist, and why are they important?

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Boston, MA? The most popular types of Bioinformatics Machine Learning jobs in Boston, MA are:
What are popular job titles related to Remote Bioinformatics Machine Learning jobs in Boston, MA? For Remote Bioinformatics Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Remote Bioinformatics Machine Learning jobs in Boston, MA look for? The top searched job categories for Remote Bioinformatics Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Remote Bioinformatics Machine Learning jobs? Cities near Boston, MA with the most Remote Bioinformatics Machine Learning job openings:
Computational Biology & Bioinformatics Lead

Computational Biology & Bioinformatics Lead

Institute for Protein Innovation

Boston, MA • On-site, Remote

Other

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago


Job description

The Institute for Protein Innovation (IPI)is a nonprofit research organization advancing protein science to accelerate research and improve human health. Founded in 2017 and located in Boston's Longwood Medical Area, the Institute's three-pronged strategy is to build protein tools, conduct related internal research and develop educational programs for the protein science and biological research communities.
With a significant endowment, IPI uniquely combines the freedom of academia with the high throughput and scale of industry to take on transformative projects. IPI has built a robust platform for discovering, developing, and distributing synthetic antibodies and other protein tools to share with the biomedical community. The Institute's deep protein expertise, collaborative spirit and research tools are powering new biomedical and therapeutic discoveries with a growing community of researchers at Harvard Medical School, Boston Children's Hospital and other institutions across Greater Boston and beyond.
Purpose
Computational Biology & Bioinformatics Lead will help grow IPI's computational protein science team and be responsible for the machine learning and data systems that support work across the Institute. This includes the following functional teams: antibody and antigen discovery, protein characterization, neuroscience, lab automation and lab operations.
This role is responsible for training and applying foundation models for protein structure prediction and design, building models that predict biophysical properties from sequence and structure and turning large multimodal biological datasets into tools and portals that can be effectively utilized across the Institute.
This position provides a combination of hands-on technical work with team leadership skills to fulfill responsibilities and achieve goals.
The position will collaborate closely with the Associate Director & Program Manager of the Antibody Platform and reports to the Senior Director of the Antibody Platform.
Primary Responsibilities
  1. Train, fine-tune, and benchmark foundation models for protein folding and design, including structure prediction models and generative models for de novo binder and antibody design, and integrate these models for routine use in antigen and antibody discovery projects.
  2. Build and validate models that predict biophysical properties such as stability, aggregation, expression, binding affinity, and developability, using multimodal data across sequence, structure, next generation sequencing, proteomics, and assay results.
  3. Run in silico binder and antibody design campaigns and pair them with experimental rounds so predictions are tested and the results feed back into the models.
  4. Develop pipelines and platforms for in vitro antibody discovery data, protein biophysical characterization, proteomics, and next generation sequencing analysis.
  5. Build and maintain web portals and databases for large biological datasets, including IPI's external antigen and antibody catalogs (for example OpenAntigens) and internal research databases.
  6. Work with teams and groups across the Institute to design experiments, interpret and analyze results, and effectively integrate computational tools into established team workflows.
  7. Manage cloud and high-performance computing environments, including GPU infrastructure for model training and large-scale analysis.
  8. Lead and mentor a small team of computational biologists and bioinformaticians.
  9. Effectively present computational analyses to technical and non-technical audiences and contribute to publications, patents, and products.
  10. Establish standards for data management, version control, reproducibility, and MLOps in the group.
Qualifications
Required
  • PhD in computational biology, bioinformatics, biophysics, machine learning, or a related field, with a strong background in protein science or biochemistry.
  • 5 or more years of relevant experience, including experience leading or mentoring computational staff or serving as a technical lead. Direct experience managing a team of two to four people is a plus.
  • Strong Python and hands-on experience with deep learning frameworks such as PyTorch.
  • Experience developing, modifying, and applying protein machine learning models for structure prediction and design.
  • Experience building or training models on multimodal biological data, with a track record shown through publications, patents, or products.
  • Experience with de novo protein and antibody design and validation cycles.

Preferred. (strong candidates will bring several of these, but not all are required)
  • Experience with next generation sequencing analysis.
  • Experience building data portals, APIs, or databases for large biological datasets.
  • Experience with cloud computing and high-performance computing or GPU environments.
  • Familiarity with antibody discovery, proteomics, or protein biophysical characterization assays.
  • Experience integrating computational predictions with wet-lab workflows, including LIMS or ELN systems.

$200,000 - $240,000 a year
IPI provides competitive compensation and an excellent benefits package to support physical, mental and financial health. Highlights of benefits include:
• 100% employer-paid medical, dental, and vision plans
• Flexible spending accounts and a healthcare reimbursement account
• 401(k) plan with generous 6% employer match - immediately 100% vested
• Generous PTO package
• Commuter and parking reimbursement
• Career development opportunities
For more information, visit proteininnovation.org or follow us on social media, @ipiproteins. IPI is an independent 501(c)(3) nonprofit research organization and an equal-opportunity employer. The Institute celebrates diversity and is committed to creating an inclusive environment for all employees. Please be advised that you will be required to provide evidence of your identity and eligibility for employment in the United States. IPI will not guarantee sponsorship of foreign nationals and retains complete discretion regarding providing sponsorship to any prospective or existing employee at time of hire or at any time in the future.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.