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

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning ... internships, undergraduate research or thesis, or substantial independent technical projects ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning ... internships, undergraduate research or thesis, or substantial independent technical projects ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Amazon

Machine Learning Engineer, Alexa AI

Boston, MA · On-site

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer ... BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ ...

Capital One

Sr. Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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All JobsMachine Learning JobsInternship Machine Learning JobsInternship Machine Learning Jobs in Boston, MA

Internship Machine Learning information

See Boston, MA salary details

$27.7K

$46.3K

$95.6K

How much do internship machine learning jobs pay per year?

As of Jul 24, 2026, the average yearly pay for internship machine learning in Boston, MA is $46,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,300.00 and $50,000.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning vs Data Science Intern?

AspectInternship Machine LearningData Science Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, programming, data analysis basics
Work EnvironmentHands-on ML model development, codingData analysis, visualization, reporting
Industry UsageTech, AI companies, research labsBusiness, finance, healthcare sectors

Internship Machine Learning focuses on developing and implementing machine learning models, requiring programming and ML fundamentals. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. Both roles are common in tech and research industries, but ML internships are more specialized in model building, while Data Science internships emphasize data analysis and visualization.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning, and why are they important?

To thrive as a Machine Learning Intern, you generally need a solid grounding in mathematics, programming (especially Python), and familiarity with machine learning concepts, often supported by coursework or relevant projects. Experience with tools and libraries like TensorFlow, scikit-learn, and Jupyter Notebooks, as well as knowledge of version control systems like Git, is typically expected. Strong problem-solving skills, willingness to learn, and effective communication set outstanding interns apart. These skills and qualities enable interns to contribute meaningfully to projects, adapt quickly, and collaborate well within technical teams.

What are internship machine learning positions?

Internship machine learning positions are temporary roles for students or recent graduates to gain hands-on experience in the field of machine learning. Interns typically work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced professionals. These internships provide valuable exposure to machine learning tools, programming languages such as Python, and industry best practices. They are an excellent way to build technical skills, enhance your resume, and explore career opportunities in artificial intelligence and data science.

What types of projects can I expect to work on during a Machine Learning internship?

As a Machine Learning intern, you may work on a variety of projects such as data preprocessing and cleaning, developing and testing machine learning models, or assisting with research experiments. These projects often involve collaborating closely with data scientists and engineers, learning to use popular frameworks like TensorFlow or PyTorch, and presenting your findings to the team. The scope and complexity of your assignments will typically grow as you demonstrate proficiency and initiative, providing valuable real-world experience and networking opportunities.
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 Internship Machine Learning jobs in Boston, MA? For Internship Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Internship Machine Learning jobs in Boston, MA look for? The top searched job categories for Internship Machine Learning jobs in Boston, MA are:
Internship Machine Learning jobs near you
Infographic showing various Internship Machine Learning job openings in Boston, MA as of July 2026, with employment types broken down into 2% Internship, 77% Full Time, 19% Part Time, 1% Temporary, and 1% Contract. Highlights an 83% Physical, 1% Hybrid, and 16% Remote job distribution, with an average salary of $46,263 per year, or $22.2 per hour.
Machine Learning Analyst

Machine Learning Analyst

Bracebridge Capital

Boston, MA

$110K - $145K/yr

Other

Posted 9 days ago

Job description

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning team. The team's primary mission is to develop machine learning systems to answer open-ended investment questions and support portfolio management decisions. The team works across the project lifecycle and technical stack, from ideation, understanding and analyzing data, hypothesis generation and testing, and model development all the way through to the deployment and maintenance of models and systems in production. Our work spans statistical modeling, classical machine learning, and modern AI and LLM techniques.

The Machine Learning Analyst's primary responsibility will be to contribute to these efforts alongside other team members. Over time, you will develop the technical and domain expertise needed to take increasing ownership of individual components and ultimately end-to-end projects.

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to translate loosely defined investment ideas into practical tools and models. Successful candidates will have solid programming foundations, be comfortable translating between qualitative and quantitative descriptions of problems and be excited to build data analysis and machine learning systems against the backdrop of portfolio management.

Since the team works closely with trading floor personnel to assist with portfolio management decision-making, an interest in economic and financial markets is essential, but no specific prior experience is necessary.

This role is open to candidates available to begin in the near term, as well as students expecting to complete their undergraduate degree between Fall 2026 and Summer 2027. Start dates will be determined based on candidate availability and, for students, degree completion.

 Responsibilities:

  • Collaborate closely with Machine Learning team members, portfolio managers, and researchers to translate open-ended investment questions into well-defined analytical and machine learning problems
  • Develop and evaluate data-driven machine learning and quantitative models, including simulation- and optimization-based approaches, for investment-related problems
  • Contribute to maintaining existing models and analytic tools in production
  • Over time, take ownership of individual features and components and full projects
  • Clearly document and communicate methods, assumptions, results, and limitations of models to other researchers and trading professionals across the firm
  • Stay current with relevant new techniques and technologies in machine learning and artificial intelligence, particularly as they pertain to finance and investing

Qualifications:

  • Bachelor's degree (or equivalent) in a rigorous quantitative field
  • 0-2 years of experience through industry internships, undergraduate research or thesis, or substantial independent technical projects involving software development, data analysis, or machine learning
  • Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas, scikit-learn, etc), with experience in other languages a plus
  • Experience working with and analyzing data from multiple sources and in multiple formats
  • Familiarity with machine learning and statistical modeling fundamentals, including model evaluation and experimental design
  • Demonstrated ability to independently scope and execute open-ended technical projects
  • Interest in financial markets, intellectual curiosity, and comfort in working on open-ended problems
  • Strong written and verbal communication skills

Current anticipated annual base salary range: $110,000 - $145,000

Base salary within the range will be determined by various factors including but not limited to the individual's experience, skills and qualifications.

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