Machine Learning Intern Jobs in Massachusetts
Machine Learning Intern jobs in Massachusetts are concentrated in Boston, Cambridge, and the Route 128 corridor, where anchor institutions like MIT, Harvard, and Mass General Brigham alongside technology companies like Google and Raytheon Technologies maintain active intern programs. The most in-demand specialties are natural language processing, computer vision, and reinforcement learning, reflecting the deep research and defense technology ecosystems here. Massachusetts ranks among the most active markets in the country for early-career machine learning talent, drawing candidates from entry-level undergrad positions to pre-doctoral research roles. 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 88 Machine Learning Intern Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
Find Machine Learning Intern JobsMachine Learning Intern Jobs by City in Massachusetts
Where Massachusetts roles are concentrated, by current openings.
Machine Learning Intern 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 intern jobs across Massachusetts.
- Currently enrolled in a bachelor's or master's program in computer science, mathematics, or statistics
- Proficiency in Python with hands-on experience using PyTorch or TensorFlow
- Demonstrated experience building and evaluating supervised or unsupervised learning models
- Familiarity with data preprocessing, feature engineering, and model validation techniques
- Experience working with large datasets using SQL, Pandas, or cloud data platforms
- Strong written and verbal communication skills for presenting findings to cross-functional teams
Machine Learning Intern Jobs in Massachusetts: Frequently Asked Questions
How do you become a machine learning intern in Massachusetts?
Machine learning internships in Massachusetts require no state-issued license or credential. The path runs through enrollment in a relevant degree program, typically computer science, data science, electrical engineering, or applied mathematics, at one of Massachusetts's many research universities. Employers in Boston and Cambridge look for candidates who can show coursework in linear algebra, probability, and programming alongside a project portfolio or research experience that demonstrates applied machine learning skills.
Which companies hire machine learning interns in Massachusetts?
Massachusetts machine learning intern roles are posted by Whoop, Wayfair, and Microsoft and others right now, based on current listings on Migrate Mate as of November 2026. Massachusetts's concentration of research hospitals, defense contractors, and technology firms means intern postings come from a wide range of employer types, from biotech companies in the Kendall Square area to aerospace and defense organizations along the Route 128 corridor.
Which Massachusetts cities have the most machine learning intern jobs?
Boston, Cambridge, and Waltham account for the largest share of machine learning intern openings in Massachusetts. Boston and Cambridge dominate because of the research university ecosystem and the technology and life sciences companies clustered around them, while suburban Route 128 cities like Waltham and Lexington draw openings from established defense and enterprise technology employers that maintain large engineering campuses there.
Are there remote machine learning intern jobs in Massachusetts?
Yes, and more than most fields. About 46% of machine learning intern openings tied to Massachusetts are remote or hybrid as of November 2026, reflecting how naturally the work translates to distributed environments. The parts of the role most likely to be fully remote are data analysis, model experimentation, and literature review, while on-site access is more commonly required for internships involving proprietary hardware, specialized computing clusters, or close lab supervision.
How can I get hired as a machine learning intern in Massachusetts with little or no experience?
The most realistic entry path is a structured university research internship, where Massachusetts institutions including MIT, Boston University, and Northeastern University run formal programs that place students with faculty or industry partners regardless of prior work experience. Candidates without a work history can strengthen their applications by contributing to open-source projects, completing Kaggle competitions, or building a portfolio on GitHub. Adjacent roles such as data analyst intern or research assistant positions at Massachusetts teaching hospitals and university labs frequently serve as the first step into applied machine learning work.
Where can I find and apply to machine learning intern jobs in Massachusetts?
You can find and apply to machine learning intern jobs in Massachusetts on Migrate Mate, which lists current Massachusetts openings updated regularly. Find the roles that fit your background and apply directly to the ones that match.
See All 88 Machine Learning Intern Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
Find Machine Learning Intern Jobs