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Junior Machine Learning Engineer Jobs in Massachusetts

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 ...

Crowe LLP

Machine Learning Engineer

Boston, MA

$62K - $100K/yr

As 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 refining and ...

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 ...

Workiva

$40/hr

Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer * Help integrate tools such as LlamaIndex and ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Massachusetts

Junior Machine Learning Engineer information

See Massachusetts salary details

$36.6K

$78.4K

$119.6K

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

As of Sep 2, 2026, the average yearly pay for junior machine learning engineer in Massachusetts is $78,414.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,000.00 and $87,400.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
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The most popular types of Machine Learning Engineer jobs in Massachusetts are:

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For Junior Machine Learning Engineer jobs in Massachusetts, the most frequently searched job titles are:

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Cities in Massachusetts with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $78,414 per year, or $37.7 per hour.

Senior Machine Learning Engineer

VideaHealth

Boston, MA • On-site

$170K - $205K/yr

Full-time

PTO

Re-posted 16 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!

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