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How much do artificial intelligence machine learning internship jobs pay per year?

As of Sep 3, 2026, the average yearly pay for artificial intelligence 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 artificial intelligence machine learning internship?

An Artificial Intelligence (AI) Machine Learning (ML) Internship is a temporary position designed for students or recent graduates to gain hands-on experience in AI and ML fields. Interns work on real-world projects involving data analysis, model development, and the application of machine learning algorithms under the guidance of experienced professionals. These internships help individuals develop practical skills, build a professional network, and improve their understanding of current technologies and tools used in AI and ML. Interns may also participate in research, code reviews, and present their findings. This experience is valuable for pursuing a career in data science, AI engineering, or related fields.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning intern?

To thrive as an Artificial Intelligence Machine Learning Intern, you need foundational knowledge in computer science, statistics, and mathematics, often supported by coursework or a degree in a related field. Familiarity with programming languages like Python, machine learning libraries such as TensorFlow or PyTorch, and experience using data analysis tools are typically required. Strong problem-solving abilities, curiosity, and effective communication skills help interns excel in collaborative, fast-paced environments. These skills and qualities are essential to contribute meaningfully to projects, learn quickly, and adapt to evolving technological challenges.

What types of projects can an artificial intelligence machine learning intern expect to work on during their internship?

As an AI/ML intern, you can expect to work on a variety of projects such as data preprocessing, model development, and performance evaluation. Interns often assist in building and testing machine learning models, analyzing large datasets, and contributing to the improvement of existing algorithms. You may also collaborate closely with data scientists, engineers, and product teams to solve real-world problems and help integrate AI solutions into business processes. These experiences provide valuable exposure to both research and practical applications in the field.

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

AspectArtificial Intelligence Machine Learning InternshipData Science Internship
Required CredentialsBasic programming, math, and AI/ML knowledgeStatistics, programming, and data analysis skills
Work EnvironmentTech companies, research labs, startupsBusiness, finance, healthcare, tech firms
Employer & Industry UsageAI/ML-focused roles in tech and researchData analysis and insights across industries
Search & Comparison IntentUnderstanding AI/ML internship roles and skillsExploring data science internship opportunities

Artificial Intelligence Machine Learning internships focus on developing AI and ML models, requiring programming and math skills. Data Science internships emphasize analyzing data to generate insights, often involving statistics and data visualization. While both roles involve data and programming, AI/ML internships are more specialized in building intelligent systems, whereas Data Science internships focus on interpreting data for decision-making.

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Artificial Intelligence Machine Learning Internship jobs near you
Infographic showing various Artificial Intelligence Machine Learning Internship job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% 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

Houston, TX

Full-time

Re-posted 13 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.

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