Machine Learning Jobs in Cambridge, MA
Machine Learning jobs in Cambridge, Massachusetts are concentrated in Kendall Square, East Cambridge, and the MIT/Harvard corridor, driven by demand from biotech, life sciences, and enterprise software employers. Roles in NLP, computer vision, and MLOps are especially active right now, and Microsoft, Lila Sciences, and Cambridge Mobile Telematics are among those currently hiring. Scan the live roles below and apply to whichever ones fit.
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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.
See All 111+ Machine Learning Jobs in Cambridge
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Find Machine Learning JobsMachine Learning Job Market in Cambridge
Who's Hiring
- Microsoft28

- Lila Sciences28

- Cambridge Mobile Telematics11

- Apple6

- Bayer6

Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Technology & Software
Machine Learning Jobs in Cambridge: Frequently Asked Questions
How do I get a machine learning job in Cambridge?
Focus your search on Kendall Square and East Cambridge, where biotech firms, AI startups, and university-affiliated research labs concentrate the most machine learning hiring. Candidates with hands-on experience in deep learning frameworks, strong GitHub portfolios, and familiarity with life sciences or enterprise software applications tend to stand out in Cambridge's market. Networking through MIT and Harvard research events also opens doors that standard applications often miss.
Which companies hire machine learnings in Cambridge?
Cambridge machine learning roles are posted by Microsoft, Lila Sciences, and Cambridge Mobile Telematics and others right now, based on current listings on Migrate Mate as of November 2026. Cambridge's employer mix is unusually research-heavy, drawing from pharmaceutical companies, AI-native startups, and university spinouts that sit alongside large technology and data analytics firms.
Are there remote machine learning jobs in Cambridge?
Yes, though availability depends heavily on the role. Analytical and modeling work is often remote-compatible, while roles tied to lab data pipelines or on-site research infrastructure tend to require in-person presence. About 62% of machine learning openings tied to Cambridge are remote or hybrid as of November 2026, with hybrid arrangements most common at the larger biotech and enterprise software employers in Kendall Square.
How can I get a machine learning job in Cambridge with little or no experience?
The most realistic entry path in Cambridge is through research assistant or junior data scientist roles at university-affiliated labs and biotech startups, which regularly hire candidates still building their portfolio. Targeting companies in East Cambridge that run structured rotational programs or co-op pipelines with MIT and Northeastern gives early-career candidates a concrete foothold. Building project experience in bioinformatics or NLP, areas where Cambridge employers concentrate, meaningfully strengthens applications over generic ML coursework alone.
Which industries hire the most machine learnings in Cambridge?
Cambridge machine learning roles concentrate in Biotechnology & Pharmaceuticals and Technology & Software, based on current listings on Migrate Mate as of November 2026. Cambridge's dense cluster of pharmaceutical companies, genomics firms, and enterprise AI startups in and around Kendall Square drives unusually strong and sustained demand compared with most U.S. metro areas.
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