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Google Machine Learning Engineer Jobs in Cambridge, MA

VideaHealth

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

Overview: The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global research and development team. This role centers on leading the design and delivery of ...

OneStudyTeam

Senior Machine Learning Engineer

Boston, MA · Remote

$140K - $190K/yr

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in building cutting-edge AI products that directly impact how new therapies reach patients. We're looking for ...

CVS Health

Senior Machine Learning Engineer

Wellesley, MA · On-site

$111K - $222K/yr

We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of data science and AI products in the journey. In this role, you'll leverage your engineering ...

Crowe-Global

Machine Learning Engineer

Boston, MA · On-site

$62 - $100/hr

About the RoleAs an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves ...

Posted today

OneScreen

Founding Machine Learning Engineer

Boston, MA · On-site

About the role You'll be the founding ML engineer who owns our matching algorithms from exploration ... Real ranking and matching modeling fluency - learning-to-rank, retrieval and re-rank patterns, not ...

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All JobsGoogle Machine Learning Engineer JobsGoogle Machine Learning Engineer Jobs in Cambridge, MA

Google Machine Learning Engineer information

See Cambridge, MA salary details

$34.4K

$140.7K

$211.5K

How much do google machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for google machine learning engineer in Cambridge, MA is $140,741.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,900.00 and $169,400.00 per year, depending on experience, location, and employer.

What is a Google machine learning engineer?

A Google Machine Learning Engineer designs, builds, and optimizes machine learning models to improve Google's products and services. They work with large datasets, implement algorithms, and deploy scalable AI systems. Collaboration with data scientists, software engineers, and product teams is essential to integrate models into real-world applications. Strong knowledge of Python, TensorFlow, and cloud computing is often required. This role focuses on both research and practical implementation to enhance automation and decision-making across Google products.

What skills and qualifications are needed to thrive as a Google machine learning engineer?

To thrive as a Google Machine Learning Engineer, you need strong expertise in mathematics, statistics, programming (especially Python or C++), and a solid background in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud), and advanced certifications can be highly beneficial. Excellent problem-solving, teamwork, and communication skills help you collaborate across teams and explain complex models to stakeholders. These skills are essential to driving innovation, building scalable solutions, and ensuring impactful results in a fast-paced, research-driven environment.

What types of projects and collaborations can Google machine learning engineers expect to be involved in?

Google Machine Learning Engineers often contribute to diverse projects, such as developing next-generation search algorithms, optimizing user experiences across products, or creating scalable machine learning systems for internal and external clients. The role frequently involves collaborating with data scientists, product managers, software engineers, and researchers to define project goals and deliver impactful solutions. You can expect to participate in code reviews, prototype new models, and provide expert input during technical discussions. This collaborative, interdisciplinary approach ensures innovative outcomes and offers ongoing opportunities for professional growth and skill development.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Cambridge, MA?

The most popular types of Google Machine Learning Engineer jobs in Cambridge, MA are:

What are popular job titles related to Google Machine Learning Engineer jobs in Cambridge, MA?

For Google Machine Learning Engineer jobs in Cambridge, MA, the most frequently searched job titles are:

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The top searched job categories for Google Machine Learning Engineer jobs in Cambridge, MA are:

Google Machine Learning Engineer jobs near you
Infographic showing various Google Machine Learning Engineer job openings in Cambridge, MA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 18% Part Time, and 11% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $140,741 per year, or $67.7 per hour.

Senior Machine Learning Engineer

VideaHealth

Boston, MA • On-site

$170K - $205K/yr

Full-time

PTO

Re-posted 4 days ago

Job description

About us:
Videa is a cutting-edge AI-powered solution for dentistry, developed by a team of seasoned leaders, engineers, AI scientists, and clinicians spun out of MIT. Our vision is to be the first company to diagnose a billion people globally. Our product is already used by thousands of dental clinicians to enhance the quality of care through faster diagnoses, to increase operating efficiencies, and to improve patient understanding.
About the position:
We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer vision teams. This is an opportunity to design, build, and scale machine learning systems that combine structured clinical data with outputs from our core computer vision models to improve patient care and operational performance.
You'll own end-to-end development of production ML systems, integrate them safely into healthcare workflows, and deploy reliable, interpretable, and monitored models that meet medical-grade standards. Depending on your background, that might mean predictive and tabular modeling, multimodal systems, large-scale training and inference infrastructure, model evaluation and reliability, or another specialty where you bring real depth. You'll work alongside ML scientists, clinical experts, and product engineers to translate real clinical questions into systems that ship and hold up over time.
We're looking for a hands-on builder who's excited to work with real-world clinical data, get models into production, and own them across their full lifecycle. If you care about impact and want to help define the future of applied AI in healthcare, we'd love to meet you.
Key Responsibilities:
  • Design, build, and deploy production ML systems for clinical decision support and operational insight, applying deep expertise from your area of specialty.
  • Develop ML pipelines that integrate structured clinical or EHR data with outputs from computer vision models to power downstream applications.
  • Ensure the calibration, robustness, and interpretability of deployed models, including clear clinician-facing explanations where relevant.
  • Implement monitoring, drift detection, evaluation protocols, and retraining or update workflows for production systems.
  • Partner cross-functionally with product, engineering, clinical, and compliance teams to define requirements and integrate models into live workflows.
  • Contribute to regulatory documentation for ML systems (data descriptions, validation reports, model versioning).
  • Mentor engineers and help establish best practices for applied ML and experimentation.
Requirements
  • 4+ years building and deploying machine learning systems in production, ideally with real-world or clinical data.
  • Deep, demonstrable expertise in at least one area of ML engineering, such as predictive and tabular modeling, multimodal systems, training and inference infrastructure, or model evaluation and reliability, along with the breadth to contribute across the stack.
  • Strong development skills in Python with testing, CI/CD, and collaborative coding practices.
  • Exceptional critical thinking and problem decomposition. Able to turn ambiguous clinical or business questions into measurable hypotheses, design sound experiments, and reason clearly about trade-offs between accuracy, reliability, interpretability, and operational impact.
  • Familiarity with production ML practices, including monitoring data drift, performance over time, and model health.
  • Excellent communication skills and a collaborative, product-oriented mindset.
Preferred
  • M.S. or Ph.D. in a relevant technical field.
  • Experience with healthcare data or regulated ML systems.
  • Background in multimodal or stacked models, especially combining CV outputs with tabular data.
  • Familiarity with survival analysis, time-series, or longitudinal modeling.
  • Open-source contributions or published work in applied ML.
  • Prior leadership or mentorship experience

What We Offer
  • Fast paced and collaborative work culture in which you can gain experience, grow your technical skills and work on a wide variety of challenges over your time with us
  • Competitive pay, equity and benefits (flexible PTO)
  • Agile organization where being senior translates to being a mentor and role model for others. We lead by example.
  • Technical challenges on the leading edge of innovation where software and machine learning intersect.

Videa is supported by some of the best investors in the world, having raised over $67M in Venture Capital from Tier 1 investors such as Spark Capital (Twitter, SnapChat, SmileDirectClub), Zetta Venture (Kaggle), and Pillar VC (PillPack), as well as angel investors such as Frederic Kerrest (Co-founder of Okta). Our work has been featured in TechCrunch, Wall Street Journal, and many other outlets.
If you want to join a breakthrough healthtech company and help accelerate its impact and growth, we encourage you to apply for this exciting opportunity!

Apply