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 ...
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Quick apply
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Machine Learning Intern information
See Flushing, NY salary details
$26.6K - $32.5K
5% of jobs
$34.5K is the 25th percentile. Wages below this are outliers.
$32.5K - $38.5K
59% of jobs
$38.5K - $44.4K
9% of jobs
$44.9K is the 75th percentile. Wages above this are outliers.
$44.4K - $50.3K
17% of jobs
$50.3K - $56.2K
4% of jobs
$56.2K - $62.2K
2% of jobs
$62.2K - $68.1K
3% of jobs
$68.1K - $74K
0% of jobs
$74K - $80K
0% of jobs
$80K - $85.9K
0% of jobs
$85.9K - $91.8K
0% of jobs
$26.6K
$44.4K
$91.8K
How much do machine learning intern jobs pay per year?
What are the key skills and qualifications needed to thrive as a machine learning intern, and why are they important?
What does a machine learning intern do?
What is the difference between Machine Learning Intern vs Data Science Intern?
| Aspect | Machine Learning Intern | Data Science Intern |
|---|---|---|
| Required Credentials | Typically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworks | Usually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills |
| Work Environment | Tech companies, research labs, startups focusing on AI/ML projects | Business, finance, healthcare, and tech sectors analyzing data for insights |
| Employer & Industry Usage | Used in companies developing AI products, research institutions, tech startups | Common in organizations requiring data analysis, reporting, and decision-making support |
While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.
What types of projects do machine learning interns typically work on, and how are they supported by the team?
What does a machine learning intern do?
A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.
- What are the career advancement opportunities for machine learning interns?
- What are the qualifications and requirements to get a machine learning internship?
- What is the difference between machine learning, artificial intelligence, and deep learning?
- What Is a Machine Learning Intern and How to Become One

Data Science Machine Learning Internship (Summer 2027)
Stamford, CT
Full-time
Posted 21 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.
About Castleton Commodities International
Sourced by ZipRecruiter
Industry
Oil and gas extraction
Company size
501 - 1,000 Employees
Headquarters location
Stamford, CT, US
Year founded
1997