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Junior Machine Learning Jobs in Boston, MA (NOW HIRING)

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 ...

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 ...

Mentor junior engineers and champion engineering excellence in ML research and development ... Industry or academic experience developing and optimizing deep learning algorithms in one or more ...

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Junior Machine Learning information

See Boston, MA salary details

$8

$29

$51

How much do junior machine learning jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for junior machine learning in Boston, MA is $29.29, according to ZipRecruiter salary data. Most workers in this role earn between $17.74 and $36.06 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 Boston, MA?

The most popular types of Machine Learning jobs in Boston, MA are:

What are popular job titles related to Junior Machine Learning jobs in Boston, MA?

For Junior Machine Learning jobs in Boston, MA, the most frequently searched job titles are:

What cities near Boston, MA are hiring for Junior Machine Learning jobs?

Cities near Boston, MA with the most Junior Machine Learning job openings:

Infographic showing various Junior Machine Learning job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $60,913 per year, or $29.3 per hour.

(Jr.) Machine Learning (ML) Developer

Laminar

Somerville, MA • On-site

$90 - $130/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New


Job description

Our pay ranges are established per Pave Compensation Software. We’re also proud to offer equity in our fast-growing startup and one of the most comprehensive benefits packages among startups at our stage. Laminar pays 100% of the individual health insurance premium for HMO medical, vision, and dental, offers flexible PTO, a $90/month transportation benefit, a $65/month health and wellness benefit, FSA, 12 company-paid holidays, an employer-matching 401(k), and Greentown Labs membership, among other valuable resources.

At Laminar (formerly H2Ok Innovations), we're leading the charge in cleantech innovation, reshaping process industrials and manufacturing to drive operational efficiency and sustainability for our world’s most foundational industries. Powered by our Laminar AI Co-pilot models and state-of-the-art sensors, our solutions optimize facility performance across various processes, including process manufacturing, production, water management, energy reduction, and waste minimization. Based at Greentown Labs, North America's premier cleantech innovation community, we're a woman-founded startup backed by renowned investors like Greycroft, Construct Capital, 2048 Ventures, and Flybridge Capital. Our groundbreaking technologies have earned accolades and adoption from industry giants like Unilever, The Coca-Cola Company, ABinBev, and Mitsubishi Electric. We're committed to unlocking untapped data for our customers, empowering them to gain a competitive edge and create Industry 4.0.

Transforming our most foundational sectors of society is hard. Very hard. But we’re building an empire. And empire building is not easy. It’s deeply fulfilling, and you will learn and grow tremendously while driving sustainable impact globally with some of the largest players that make everything we eat, use, and wear. Our culture is to foster extraordinary growth within our teammates. We believe in autonomy, ownership, empowerment, demanding excellence, being mission-driven. We believe in creativity, authenticity, and extraordinary growth. We’re looking for relentless, ambitious, creative, and exceptional people to join our team and build the factory of the future.

What You Will Do

Build machine learning models that usher in the next generation of data-driven, fluid-based industrial processes powered by Laminar's proprietary spectral sensors and software platform.

Design and run experiments to evaluate and select machine learning models that are generalizable, accurate, and robust to day-to-day process variability.

Work with spectral and multi‑modal sensor data, building preprocessing and feature extraction pipelines that can derive insights from noisy, real‑world sensors.

Support model reliability by developing monitoring (and correction systems, when applicable) for model drift, sensor drift, and process anomalies.

Develop performant ML infrastructure and tooling in collaboration with ML/Data Scientists and software team members.

Work across problem domains including chemometrics, hybrid modeling, and self-supervised learning. Modeling tasks include distribution modeling, drift and anomaly detections, similarity analyses, and continuous calibration.

About You

Required:

  • Proficient in at least one Python ML framework (PyTorch, JAX, TensorFlow).
  • Fluent with Python packages for numeric computing and data workflows (NumPy, Polars, Pandas, scikit-learn).
  • An engineer who favors clean, testable code and has a proven track record of delivering high-quality work on a timeline.
  • An executor who thrives with direction and can independently complete technical project objectives.
  • Someone detail-oriented who has a natural curiosity about data. You are enthusiastic to test hypotheses, understand in detail how our models work, and run physical experiments to improve our modeling capabilities.

Preferred:

  • Chemical engineering, process engineering, or manufacturing domain knowledge (highly valued).
  • Experience with cloud environments (AWS, GCP) and/or Databricks.
  • Familiarity with spectral data, time‑series modeling, or sensor-driven ML.
  • Familiarity with Bayesian modeling and probabilistic reasoning.
  • Experience building real products (ideally utilizing machine learning) and practicing user‑centric design.

Benefits:

  • Direct impact on product and culture.
  • Comprehensive benefits package including Medical, Dental, Vision, Life Insurance, Disability, Transportation benefit, Health and Wellness benefit, and more.
  • 401(k) plan with employer matching.
  • Equity.
  • Competitive salary and bonus opportunities.
  • Dynamic and inclusive work environment.
  • Opportunities for growth and professional development.
  • Access to Greentown Labs' extensive network of cleantech startups.
Why Laminar (formerly H2Ok Innovations)?

Impact: Work on cutting‑edge AI and sensor tech that’s already transforming how factories use water, energy, and chemicals. Join a tight‑knit, ambitious team where your contributions can reshape the industry.

Growth: Join a fast‑growing startup where you’ll have the opportunity to shape our content strategy. We value fostering extraordinary growth in our teammates.

Innovative Culture: Work in a high-performance environment that values empowerment, creativity, ownership, autonomy, innovation, excellence, passion, and continuous growth.

Sustainability Focus: Play a key role in promoting sustainability and Industry 4.0 advancements in manufacturing.

Build the intelligence layer powering the next generation of industrial efficiency – with a team that moves fast and delivers real impact.

* We recently updated our domain to runlaminar.com. Please ensure you add the runlaminar.com domain to your safe senders list to ensure you receive our communications.

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