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Junior Machine Learning Jobs in Massachusetts (NOW HIRING)

$93K - $149K/yr

Leadership and Mentorship: • Experience mentoring junior engineers and providing guidance on best ... machine learning projects.

Provide technical leadership to junior scientists, guiding the transition of R&D concepts into ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Provide technical leadership to junior scientists, guiding the transition of R&D concepts into ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Our Health Machine Learning team develops the algorithms and models that power health features used ... Develop the next layer of leadership, coach junior and seniorICs, manage performance with clarity ...

Independently apply productized AI and Machine Learning models to advance 1910's active drug design campaigns * Independently write and publish peer reviewed scientific articles and mentor junior AI ...

... junior researchers. Responsibilities : • Propose and prototype AI and Machine Learning solutions that address use cases in 1910's design pipeline • Independently apply productized AI and Machine ...

... Machine Learning models to advance 1910's active drug design campaigns • Independently write and publish peer reviewed scientific articles and mentor junior AI Researchers with their work • ...

... Machine Learning models to advance 1910's active drug design campaigns • Independently write and publish peer reviewed scientific articles and mentor junior AI Researchers with their work • ...

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Junior Machine Learning information

See Massachusetts salary details

$8

$29

$51

How much do junior machine learning jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for junior machine learning in Massachusetts is $29.44, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $36.25 per hour, depending on experience, location, and employer.

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Massachusetts?

The most popular types of Machine Learning jobs in Massachusetts are:

What cities in Massachusetts are hiring for Junior Machine Learning jobs?

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

Infographic showing various Junior Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $61,234 per year, or $29.4 per hour.

$93K - $149K/yr

Full-time

Re-posted 21 days ago


Job description

Job Posting Description
Position Summary
The ML Ops Engineer II at Boston Children's Hospital is an integral part of the Data Science team within Enterprise Data & Analytics in BCH IT. This role is pivotal in developing and scaling advanced AI and machine learning projects, enhancing data frameworks, and optimizing data flows to support the hospital's strategic initiatives. The ML Ops Engineer II works in close collaboration with data scientists and various stakeholders across the hospital to develop solutions that improve patient care outcomes and operational efficiency. Focused on innovation and technological advancement, the ML Ops Engineer II ensures the robust integration of data science into clinical and administrative processes. Key Responsibilities
Technical Skills:
• Proficient in SQL and an understanding of database management systems.
• Familiarity with ETL tools; experience with debt is highly advantageous.
• Strong capabilities in Python or another advanced scripting language, essential for AI and machine learning model development.
• Experience with cloud-based data platforms and tools such as AWS, Azure, or GCP is a plus.
Analytical Skills:
• Strong problem-solving abilities and adeptness in handling complex data sets.
• Ability to apply analytical rigor to understand, interpret, and leverage data to drive decision-making.
Project Management Skills:
• Demonstrated experience in managing multiple projects, including developing project plans, tracking progress, and adjusting resources and timelines.
• Ability to coordinate efforts across different teams and ensure project milestones are met.
Leadership and Mentorship:
• Experience mentoring junior engineers and providing guidance on best practices in data engineering and AI model development.
• Ability to lead code reviews and foster a collaborative and innovative team environment.
Communication:
• Excellent interpersonal and communication skills, essential for effective collaboration with cross-functional teams.
• Capable of clearly articulating technical concepts to non-technical stakeholders, ensuring alignment and understanding across diverse teams
Education
  • Bachelor's Degree or comparable experience required
  • Master's Degreepreferred

Experience:
3-5 years of relevant experience in data engineering, including project leadership responsibilities and advanced technical contributions to AI or machine learning projects.