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Undergraduate Machine Learning Internship Jobs (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY

Many classes and activities are shared with our Software Engineering interns, while others focus ... An undergraduate or PhD student with practical experience training an ML model, working on an ML ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus ... An undergraduate or PhD student with practical experience training an ML model, working on an ML ...

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 ...

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Undergraduate Machine Learning Internship information

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$25.5K

$42.6K

$88K

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

As of Aug 15, 2026, the average yearly pay for undergraduate machine learning internship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is an undergraduate machine learning internship?

An Undergraduate Machine Learning Internship is a temporary position designed for students pursuing a bachelor's degree who want hands-on experience in machine learning. Interns typically work on real-world projects involving data preprocessing, model development, and performance evaluation under the guidance of experienced engineers or researchers. They may also assist with research, implement algorithms, and optimize models for deployment. The role helps students gain practical skills in coding, data analysis, and machine learning frameworks while preparing them for future careers in AI and data science.

What are the key skills and qualifications needed to thrive in an undergraduate machine learning internship, and why are they important?

To thrive as an Undergraduate Machine Learning Intern, you typically need a strong foundation in mathematics, statistics, and programming (Python or R), often supported by ongoing studies in computer science, data science, or a related field. Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch, and familiarity with data analysis tools are commonly valued. Curiosity, strong problem-solving abilities, and the willingness to work collaboratively in a team make candidates stand out. These skills and qualities are crucial for learning quickly, making meaningful contributions to real projects, and growing in a fast-paced, technical environment.

What types of projects or tasks can I expect to work on during an undergraduate machine learning internship?

As an Undergraduate Machine Learning Intern, you can expect to assist with tasks such as data preprocessing, model development and evaluation, and implementing machine learning algorithms under the guidance of experienced team members. You may also be involved in cleaning and exploring data sets, creating visualizations, and helping automate parts of the data pipeline. Collaborating with data scientists and engineers, you’ll likely participate in team meetings, code reviews, and brainstorming sessions to address real-world business or research challenges. These hands-on experiences are designed to help you build practical skills and gain exposure to the workflow of professional machine learning projects.

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Undergraduate Machine Learning Internship jobs near you
Infographic showing various Undergraduate Machine Learning Internship job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

Full-time

Posted 26 days ago

Job description

Application Deadline: September 1, 11:59pm EST
Program Summary - Commercial Technology Internships
Company Overview:
Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.
Position Overview:
CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.
Responsibilities:
  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:
  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

Apply