Senior ML Engineer Visa Sponsorship Jobs in Massachusetts
Massachusetts is one of the strongest markets for senior ML engineer visa sponsorship in the U.S., driven by Boston's dense concentration of AI research institutions, biotech firms, and enterprise tech companies. Major employers include Amazon, Google, Microsoft, and a growing cluster of ML-focused startups and academic spinouts headquartered in Cambridge and the Greater Boston area.
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Get Access To All JobsINTRODUCTION
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
JOB SUMMARY
The Microbiome AI/Deep Learning Lab in the Massachusetts Host-Microbiome Center and Division of Computational Pathology at Brigham and Women’s Hospital/Harvard Medical School is seeking a computational scientist with experience in microbiome bioinformatics and machine learning. You will develop, deploy, and apply microbiome and bioinformatics machine learning approaches, with a special emphasis on deep learning, to a variety of microbiology data sources. Applications will include forecasting microbial population dynamics in the gut, characterizing the impact of spatial structure of the microbiome, predicting impact of the microbiome on host phenotype, tracking infections in human populations, elucidating microbial metabolism, and discovering functions of uncharacterized microbial metabolites and proteins.
QUALIFICATIONS
A COVER LETTER IS REQUIRED FOR ALL APPLICATIONS.
Applicants Should Have a High Level Of Interest In
- A long-term career in an academic medical environment, with the potential for your work to have a direct impact on healthcare outcomes.
- Applying new deep learning technologies to biomedical problems.
- Advancing knowledge of the microbiome and its role in human health and disease.
- Working on an interdisciplinary team and collaborating with computational, wet lab and clinical scientists.
- Engaging with the broader research community to advance applications of AI/deep learning for the microbiome.
ABOUT THE ENVIRONMENT
The Microbiome AI/Deep Learning Lab is an initiative within the Massachusetts Host-Microbiome Center (MHMC) and the Division of Computational Pathology (DCP) at Brigham and Women’s Hospital (BWH)/Harvard Medical School. With recent funding from the Massachusetts Life Sciences Center, the Lab has built a state-of-the-art compute cluster with extensive GPU and CPU nodes, with the objective of making advanced deep learning technologies broadly available to microbiome researchers. The MHMC is a research and core facility that has worked with 100+ groups in the US and internationally to promote understanding of host-microbiome interactions in health and disease, emphasizing a focus on function to define causative effects of the microbiota and to harness this knowledge in developing new therapies, diagnostics and further commercial applications. The DCP is a research division with a broad mandate to develop and apply advanced computational methods for furthering the understanding, diagnosis and treatment of human diseases. BWH is an HMS affiliated teaching hospital, adjacent to the HMS main quad, and the second largest non-university recipient of NIH research funding.
PRINCIPAL DUTIES AND RESPONSIBILITIES
- Engage in research developing and applying bioinformatic and machine learning approaches, for a variety of microbiology data sources, including next generation sequencing and metabolomic data.
- Substantially contribute to scientific publications and grant applications.
- Analyze datasets and produce visualizations and written reports about scientific findings.
- Deploy computational pipelines on local workstations and on high performance CPU and GPU clusters.
- Organize and curate large datasets using structured approaches, including database systems.
- Engage with trainees and other users of the MHMC to facilitate use of computing resources and application of machine learning technologies for the microbiome.
- Other duties as assigned.
ADDITIONAL JOB DETAILS
- Data Science experience with PhD 2-3 years required or Data Science experience with a Master's 3-5 years required.
- Experience analyzing microbiome data and machine learning applications demonstrated through authorship on high-quality, peer-reviewed scientific publications.
- 3+ years minimum Python programming experience preferred.
- 3+ years minimum experience working in high-performance computing environments preferred.
- Experience with microbiome bioinformatics methods and pipelines for next generation sequencing data analysis.
- Experience with organizing and managing large multi-omics datasets.
- Strong verbal and written communication, and interpersonal skills.
- Experience with deep learning and PyTorch is highly desired.
SKILLS/ABILITIES/COMPETENCIES REQUIRED
- Must be capable of contributing within an interdisciplinary team, exhibit a high level of initiative, and have an eagerness to learn new technologies.
- Ability to manage entire projects in a research environment, from design to implementation, and interpretation of final results.
- Must have experience analyzing microbiome data.
- Must possess advanced knowledge of machine learning, including model development, training, testing and deploying.
- Demonstrated ability to develop and implement computational approaches for analyzing complex biomedical datasets including next generation sequencing data.
- Demonstrated ability to manage large and complex biomedical datasets, using tools such as databases.
- Excellent written and verbal communication skills with demonstrated ability to communicate complex results to both technical and non-technical audiences, through publications and presentations.
- Ability to implement machine learning methods in Python; experience with deep learning and using PyTorch is highly desired.
- Knowledge of software engineering best practices, including source code management/control (e.g., Git) and containerization approaches.
- Experience with high-performance computing environments, including scheduling systems, e.g., SLURM.
- Ability to multitask and prioritize work, to achieve desired goals and deliverables.
- Ability to share expertise, coach, and give general direction to others of different skill sets, backgrounds and levels.
REMOTE TYPE
Onsite
WORK LOCATION
60 Fenwood Road
SCHEDULED WEEKLY HOURS
40
EMPLOYEE TYPE
Regular
WORK SHIFT
Day (United States of America)
PAY RANGE
$93,953.60 - $136,739.20/Annual
GRADE
7
At Mass General Brigham, we believe in recognizing and rewarding the unique value each team member brings to our organization. Our approach to determining base pay is comprehensive, and any offer extended will take into account your skills, relevant experience if applicable, education, certifications and other essential factors. The base pay information provided offers an estimate based on the minimum job qualifications; however, it does not encompass all elements contributing to your total compensation package. In addition to competitive base pay, we offer comprehensive benefits, career advancement opportunities, differentials, premiums and bonuses as applicable and recognition programs designed to celebrate your contributions and support your professional growth. We invite you to apply, and our Talent Acquisition team will provide an overview of your potential compensation and benefits package.
EEO STATEMENT
2200 The Brigham and Women's Hospital, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
MASS GENERAL BRIGHAM COMPETENCY FRAMEWORK
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.
INTRODUCTION
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
JOB SUMMARY
The Microbiome AI/Deep Learning Lab in the Massachusetts Host-Microbiome Center and Division of Computational Pathology at Brigham and Women’s Hospital/Harvard Medical School is seeking a computational scientist with experience in microbiome bioinformatics and machine learning. You will develop, deploy, and apply microbiome and bioinformatics machine learning approaches, with a special emphasis on deep learning, to a variety of microbiology data sources. Applications will include forecasting microbial population dynamics in the gut, characterizing the impact of spatial structure of the microbiome, predicting impact of the microbiome on host phenotype, tracking infections in human populations, elucidating microbial metabolism, and discovering functions of uncharacterized microbial metabolites and proteins.
QUALIFICATIONS
A COVER LETTER IS REQUIRED FOR ALL APPLICATIONS.
Applicants Should Have a High Level Of Interest In
- A long-term career in an academic medical environment, with the potential for your work to have a direct impact on healthcare outcomes.
- Applying new deep learning technologies to biomedical problems.
- Advancing knowledge of the microbiome and its role in human health and disease.
- Working on an interdisciplinary team and collaborating with computational, wet lab and clinical scientists.
- Engaging with the broader research community to advance applications of AI/deep learning for the microbiome.
ABOUT THE ENVIRONMENT
The Microbiome AI/Deep Learning Lab is an initiative within the Massachusetts Host-Microbiome Center (MHMC) and the Division of Computational Pathology (DCP) at Brigham and Women’s Hospital (BWH)/Harvard Medical School. With recent funding from the Massachusetts Life Sciences Center, the Lab has built a state-of-the-art compute cluster with extensive GPU and CPU nodes, with the objective of making advanced deep learning technologies broadly available to microbiome researchers. The MHMC is a research and core facility that has worked with 100+ groups in the US and internationally to promote understanding of host-microbiome interactions in health and disease, emphasizing a focus on function to define causative effects of the microbiota and to harness this knowledge in developing new therapies, diagnostics and further commercial applications. The DCP is a research division with a broad mandate to develop and apply advanced computational methods for furthering the understanding, diagnosis and treatment of human diseases. BWH is an HMS affiliated teaching hospital, adjacent to the HMS main quad, and the second largest non-university recipient of NIH research funding.
PRINCIPAL DUTIES AND RESPONSIBILITIES
- Engage in research developing and applying bioinformatic and machine learning approaches, for a variety of microbiology data sources, including next generation sequencing and metabolomic data.
- Substantially contribute to scientific publications and grant applications.
- Analyze datasets and produce visualizations and written reports about scientific findings.
- Deploy computational pipelines on local workstations and on high performance CPU and GPU clusters.
- Organize and curate large datasets using structured approaches, including database systems.
- Engage with trainees and other users of the MHMC to facilitate use of computing resources and application of machine learning technologies for the microbiome.
- Other duties as assigned.
ADDITIONAL JOB DETAILS
- Data Science experience with PhD 2-3 years required or Data Science experience with a Master's 3-5 years required.
- Experience analyzing microbiome data and machine learning applications demonstrated through authorship on high-quality, peer-reviewed scientific publications.
- 3+ years minimum Python programming experience preferred.
- 3+ years minimum experience working in high-performance computing environments preferred.
- Experience with microbiome bioinformatics methods and pipelines for next generation sequencing data analysis.
- Experience with organizing and managing large multi-omics datasets.
- Strong verbal and written communication, and interpersonal skills.
- Experience with deep learning and PyTorch is highly desired.
SKILLS/ABILITIES/COMPETENCIES REQUIRED
- Must be capable of contributing within an interdisciplinary team, exhibit a high level of initiative, and have an eagerness to learn new technologies.
- Ability to manage entire projects in a research environment, from design to implementation, and interpretation of final results.
- Must have experience analyzing microbiome data.
- Must possess advanced knowledge of machine learning, including model development, training, testing and deploying.
- Demonstrated ability to develop and implement computational approaches for analyzing complex biomedical datasets including next generation sequencing data.
- Demonstrated ability to manage large and complex biomedical datasets, using tools such as databases.
- Excellent written and verbal communication skills with demonstrated ability to communicate complex results to both technical and non-technical audiences, through publications and presentations.
- Ability to implement machine learning methods in Python; experience with deep learning and using PyTorch is highly desired.
- Knowledge of software engineering best practices, including source code management/control (e.g., Git) and containerization approaches.
- Experience with high-performance computing environments, including scheduling systems, e.g., SLURM.
- Ability to multitask and prioritize work, to achieve desired goals and deliverables.
- Ability to share expertise, coach, and give general direction to others of different skill sets, backgrounds and levels.
REMOTE TYPE
Onsite
WORK LOCATION
60 Fenwood Road
SCHEDULED WEEKLY HOURS
40
EMPLOYEE TYPE
Regular
WORK SHIFT
Day (United States of America)
PAY RANGE
$93,953.60 - $136,739.20/Annual
GRADE
7
At Mass General Brigham, we believe in recognizing and rewarding the unique value each team member brings to our organization. Our approach to determining base pay is comprehensive, and any offer extended will take into account your skills, relevant experience if applicable, education, certifications and other essential factors. The base pay information provided offers an estimate based on the minimum job qualifications; however, it does not encompass all elements contributing to your total compensation package. In addition to competitive base pay, we offer comprehensive benefits, career advancement opportunities, differentials, premiums and bonuses as applicable and recognition programs designed to celebrate your contributions and support your professional growth. We invite you to apply, and our Talent Acquisition team will provide an overview of your potential compensation and benefits package.
EEO STATEMENT
2200 The Brigham and Women's Hospital, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
MASS GENERAL BRIGHAM COMPETENCY FRAMEWORK
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.
Senior ML Engineer Job Roles in Massachusetts
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Search Senior ML Engineer Jobs in MassachusettsSenior ML Engineer Jobs in Massachusetts: Frequently Asked Questions
Which companies sponsor visas for senior ML engineers in Massachusetts?
Major sponsors in Massachusetts include Amazon, Google, Microsoft, HubSpot, Wayfair, and a large number of biotech and AI startups concentrated in Cambridge and Boston. Academic medical centers like Mass General Brigham also hire senior ML engineers for applied research roles. Sponsorship patterns are most consistent at mid-to-large tech employers with established immigration programs and dedicated HR infrastructure.
Which visa types are most common for senior ML engineer roles in Massachusetts?
The H-1B visa is the most common visa for senior ML engineers in Massachusetts, as the role qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, machine learning, or a related field. Australian citizens may pursue the E-3 visa. Candidates with extraordinary ability in AI research sometimes qualify for the O-1A. Employers at universities or affiliated research institutions may also file cap-exempt H-1B visa petitions.
Which cities in Massachusetts have the most senior ML engineer sponsorship jobs?
Cambridge and Boston together account for the overwhelming majority of senior ML engineer sponsorship jobs in Massachusetts. Cambridge hosts Kendall Square, one of the densest concentrations of AI and biotech employers in the country, including MIT spinouts and major tech office locations. Somerville, Waltham, and Burlington also have active employer clusters, particularly in enterprise software, defense technology, and healthcare analytics.
How to find senior ml engineer visa sponsorship jobs in Massachusetts?
Migrate Mate filters job listings specifically for roles that include visa sponsorship, so you can browse senior ML engineer positions in Massachusetts without sorting through companies that won't support international candidates. The platform is built for this use case, covering employers across Boston, Cambridge, and surrounding areas. Searching by role and state on Migrate Mate surfaces opportunities at both established tech employers and high-growth AI startups.
Are there state-specific considerations for senior ML engineers pursuing sponsorship in Massachusetts?
Massachusetts employers filing H-1B petitions must meet Department of Labor prevailing wage requirements for the Boston-Cambridge-Nashua metropolitan area, which reflects a high cost of living and competitive local market. The state's deep university pipeline, including MIT, Harvard, and Northeastern, creates strong employer familiarity with visa sponsorship processes. Biotech and AI research roles in the area often intersect with federal grant funding, which can affect hiring timelines and visa eligibility at some institutions.
What is the prevailing wage for sponsored senior ml engineer jobs in Massachusetts?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.