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Machine Learning Summer Internship Jobs in Boston, MA

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

... Summer 2027. Start dates will be determined based on candidate availability and, for students ... internships, undergraduate research or thesis, or substantial independent technical projects ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

... Summer 2027. Start dates will be determined based on candidate availability and, for students ... 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 Summer JobsMachine Learning Summer Internship JobsMachine Learning Summer Internship Jobs in Boston, MA

Machine Learning Summer Internship information

See Boston, MA salary details

$27.7K

$46.3K

$95.6K

How much do machine learning summer internship jobs pay per year?

As of Jul 26, 2026, the average yearly pay for machine learning summer internship 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 are the key skills and qualifications needed to thrive as a Machine Learning Summer Intern, and why are they important?

To thrive as a Machine Learning Summer Intern, you need a solid background in mathematics, statistics, and programming (especially Python), often supported by ongoing coursework in computer science or related fields. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems such as Git, and data analysis tools is typically required. Strong problem-solving skills, curiosity, and teamwork are important soft skills that help interns contribute effectively and learn quickly. These skills and qualities are crucial for applying theoretical knowledge, collaborating on real projects, and adapting to the fast-evolving field of machine learning.

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

As a Machine Learning Summer Intern, you can expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of algorithms into production environments. Interns often work alongside data scientists and engineers on real-world datasets to solve business problems, develop prototypes, or improve existing models. This hands-on experience will help you gain practical skills in using popular ML frameworks and understanding the end-to-end machine learning workflow.

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

AspectMachine Learning Summer InternshipData Science Summer Internship
Required CredentialsBasic programming, math, and machine learning knowledgeProgramming, statistics, and data analysis skills
Work EnvironmentDeveloping ML models, algorithms, and prototypesData analysis, visualization, and reporting
Industry UsageTech companies, AI startups, research labsBusiness, finance, healthcare, tech firms

Both internships involve working with data and require programming skills, but Machine Learning Summer Internships focus on developing algorithms and models, while Data Science Summer Internships emphasize data analysis and insights. The choice depends on your interest in building models versus analyzing data.

What is a Machine Learning Summer Internship?

A Machine Learning Summer Internship is a temporary, typically 8-12 week program for students or recent graduates to gain practical experience in machine learning. Interns work under the supervision of experienced professionals, contributing to real-world projects involving data analysis, model development, and algorithm implementation. These internships often provide mentorship, networking opportunities, and exposure to the latest tools and technologies in the field. They are valuable for building technical skills and improving career prospects in artificial intelligence and data science.
What are popular job titles related to Machine Learning Summer Internship jobs in Boston, MA? For Machine Learning Summer Internship jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Summer Internship jobs in Boston, MA look for? The top searched job categories for Machine Learning Summer Internship jobs in Boston, MA are:
What cities near Boston, MA are hiring for Machine Learning Summer Internship jobs? Cities near Boston, MA with the most Machine Learning Summer Internship job openings:
Machine Learning Summer Internship jobs near you
Infographic showing various Machine Learning Summer Internship job openings in Boston, MA as of July 2026, with employment types broken down into 2% Internship, 74% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% 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 11 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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