Machine Learning Manager Jobs in Massachusetts
Machine Learning Manager jobs in Massachusetts are among the most active in the country, concentrated in life sciences, financial technology, and enterprise software, with demand at every level from lead ML engineer moving into management through senior director of machine learning. Boston, Cambridge, and Waltham are the primary hiring hubs, anchored by employers like Fidelity Investments, Biogen, and MathWorks, who maintain long-term machine learning teams. The most in-demand specialties are MLOps and model deployment, healthcare AI, and NLP for financial services. Find a role that fits below and apply directly.
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Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about making AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Senior Machine Learning Engineer to help shape the future of responsible AI evaluation for the next generation of generative features.
In this role, you will work to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. Your work will tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apple's values, privacy, and quality standards.
As part of Apple’s Responsible AI group within the Software Engineering organization, you’ll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You’ll anticipate safety risks and deliver trusted, high-quality AI experiences to users around the globe.
Description
We are seeking a visionary Senior Machine Learning Engineer to drive Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical execution for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and implementing robust data pipelines to produce reliable, scalable insights that inform ship/no-ship product decisions.
Pre- and post-launch, you will be deeply hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a senior technical leader on the team, you will champion technical excellence, empower leadership with data-driven safety recommendations, and systematically solve complex engineering roadblocks. This role heavily draws on applied data science, scientific investigation, cross-functional collaboration, and defending safety metrics to stakeholders and decision-makers.
Preferred Qualifications
Experience working with multimodal models, agentic systems, and/or diverse languages and locales
Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots
Experience conducting large scale benchmarking across models and capabilities
Minimum Qualifications
Develop metrics for the evaluation of safety and fairness risks inherent to generative models and Gen-AI features.
Design datasets, identify data needs, and implement creative solutions to scale and expand data coverage through human and synthetic generation methods.
Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale.
Design, implement, and optimize data pipelines, collaborating cross-functionally to execute end-to-end safety evaluations.
Drive operational excellence by automating manual workflows and optimizing evaluation velocity to meet rapid product release cycles.
Distill complex project findings into actionable insights for product engineering teams and safety policy development.
Work with highly-sensitive content, including exposure to offensive and controversial material.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $165,800 and $292,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about making AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Senior Machine Learning Engineer to help shape the future of responsible AI evaluation for the next generation of generative features.
In this role, you will work to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. Your work will tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apple's values, privacy, and quality standards.
As part of Apple’s Responsible AI group within the Software Engineering organization, you’ll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You’ll anticipate safety risks and deliver trusted, high-quality AI experiences to users around the globe.
Description
We are seeking a visionary Senior Machine Learning Engineer to drive Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical execution for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and implementing robust data pipelines to produce reliable, scalable insights that inform ship/no-ship product decisions.
Pre- and post-launch, you will be deeply hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a senior technical leader on the team, you will champion technical excellence, empower leadership with data-driven safety recommendations, and systematically solve complex engineering roadblocks. This role heavily draws on applied data science, scientific investigation, cross-functional collaboration, and defending safety metrics to stakeholders and decision-makers.
Preferred Qualifications
Experience working with multimodal models, agentic systems, and/or diverse languages and locales
Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots
Experience conducting large scale benchmarking across models and capabilities
Minimum Qualifications
Develop metrics for the evaluation of safety and fairness risks inherent to generative models and Gen-AI features.
Design datasets, identify data needs, and implement creative solutions to scale and expand data coverage through human and synthetic generation methods.
Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale.
Design, implement, and optimize data pipelines, collaborating cross-functionally to execute end-to-end safety evaluations.
Drive operational excellence by automating manual workflows and optimizing evaluation velocity to meet rapid product release cycles.
Distill complex project findings into actionable insights for product engineering teams and safety policy development.
Work with highly-sensitive content, including exposure to offensive and controversial material.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $165,800 and $292,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See All 89 Machine Learning Manager Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
Find Machine Learning Manager JobsMachine Learning Manager Jobs by City in Massachusetts
Where Massachusetts roles are concentrated, by current openings.
Machine Learning Manager Job Market in Massachusetts
A snapshot from current Massachusetts openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Automotive
- Biotechnology & Pharmaceuticals
- Medical Devices
- Artificial Intelligence
What Massachusetts Employers Look For
The qualifications that appear most often in machine learning manager jobs across Massachusetts.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Three or more years managing machine learning engineers or data scientists in a production environment
- Hands-on experience with Python, PyTorch, or TensorFlow alongside team leadership responsibilities
- Demonstrated ability to deploy and monitor ML models at scale in cloud environments such as AWS or Azure
- Experience collaborating with product and engineering stakeholders to translate business problems into ML solutions
- Familiarity with MLOps practices including CI/CD pipelines, model versioning, and experiment tracking frameworks
Machine Learning Manager Jobs in Massachusetts: Frequently Asked Questions
How do you become a machine learning manager in Massachusetts?
Machine learning manager roles in Massachusetts do not require a state-issued license or registration. The typical path is a bachelor's or master's degree in computer science, applied mathematics, or a related field, followed by several years as an individual-contributor ML engineer or data scientist. Massachusetts employers, particularly in biotech and fintech, place strong weight on a portfolio of shipped models and prior experience mentoring junior engineers before promoting or hiring into a management role.
Which companies hire machine learning managers in Massachusetts?
Employers hiring machine learning managers in Massachusetts right now include Whoop, Wayfair, and Microsoft, based on current listings on Migrate Mate as of November 2026. Massachusetts's dense concentration of life sciences companies, asset managers, and enterprise software firms means hiring tends to be consistent year-round rather than tied to seasonal surges.
Which Massachusetts cities have the most machine learning manager jobs?
Boston, Cambridge, and Waltham have the most machine learning manager openings in Massachusetts. Boston and Cambridge dominate because of the biotech corridor along Kendall Square and the financial services firms headquartered downtown, while Waltham draws openings from the Route 128 technology belt where companies like MathWorks and several Fidelity divisions are based.
Are there remote machine learning manager jobs in Massachusetts?
Yes, and more than most fields. About 46% of machine learning manager openings tied to Massachusetts are remote or hybrid as of November 2026, reflecting how much of the work centers on code review, model evaluation, and cross-functional meetings that travel well over video. The most fully remote roles tend to be at companies whose engineering teams are already distributed, while hybrid arrangements are more common at life sciences firms that expect on-site collaboration during model validation cycles.
How can I get hired as a machine learning manager in Massachusetts with little or no experience?
The most realistic entry path is transitioning from a senior individual-contributor role, specifically senior data scientist or senior ML engineer, into a team-lead position at a Massachusetts employer before stepping into a full manager title. Large Boston-area employers in biotech and fintech regularly post ML tech-lead or staff engineer roles that carry informal people-management responsibilities and serve as proving grounds. Building a public portfolio of end-to-end projects, contributing to open-source ML tooling, and completing a formal ML specialization through an accredited program strengthens candidacy significantly for first-time managers.
Where can I find and apply to machine learning manager jobs in Massachusetts?
You can find and apply to machine learning manager jobs in Massachusetts on Migrate Mate, which lists current Massachusetts openings. Find the roles that fit your background and apply directly from the listings on this page.
See All 89 Machine Learning Manager Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
Find Machine Learning Manager Jobs