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Internship Graduate Machine Learning Jobs in Massachusetts

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 ...

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 ...

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 ...

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or ... Previous software engineering experience via an internship, work experience, or coding competition

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+ ...

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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Internship Graduate Machine Learning information

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

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

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What are Internship Graduate Machine Learning positions?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do Internship Graduate Machine Learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.
What cities in Massachusetts are hiring for Internship Graduate Machine Learning jobs? Cities in Massachusetts with the most Internship Graduate Machine Learning job openings:
Infographic showing various Internship Graduate Machine Learning job openings in Massachusetts as of July 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution.

$110K - $145K/yr

Other

Posted 17 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.