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Machine Learning Internship Opt Cpt Jobs in Texas

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

... Internship experience does not apply) * At least 4 years of experience programming with Python ... H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

... Internship experience does not apply) * At least 4 years of experience programming with Python ... H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of ...

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Machine Learning Internship Opt Cpt information

What kinds of projects or tasks can a machine learning intern expect to work on during an internship?

As a Machine Learning intern, you can expect to be involved in projects such as data preprocessing, exploratory data analysis, model building, and performance evaluation. Interns often work with real datasets, contribute to feature engineering, and assist in deploying models or creating proof-of-concept solutions. Collaboration with data scientists, engineers, and sometimes product teams is common, providing valuable insights into real-world machine learning workflows. This hands-on experience helps interns build technical skills and gain exposure to best practices in the field.

What is a machine learning internship OPT CPT?

A Machine Learning Internship OPT CPT refers to an internship opportunity in the field of machine learning that is specifically available to international students in the U.S. on F-1 visas, who are eligible for Optional Practical Training (OPT) or Curricular Practical Training (CPT). These internships allow students to gain hands-on experience applying machine learning techniques in real-world projects while meeting their academic requirements or career goals. The roles typically involve tasks such as data analysis, building predictive models, and working with large datasets using programming languages like Python or R. OPT is usually used after graduation, while CPT is often part of the academic curriculum during the degree program.

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

AspectMachine Learning Internship Opt CptData Science Internship
Required CredentialsTypically requires coursework or experience in machine learning, programming, and statisticsRequires knowledge in statistics, data analysis, and programming, often with a focus on data manipulation
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBroad industry sectors including finance, healthcare, tech, with data analysis focus
Employer & Industry UsageUsed by companies developing AI/ML products and servicesUsed across industries for data-driven decision making

While both internships involve working with data, the Machine Learning Internship Opt Cpt focuses on developing algorithms and models, whereas Data Science Internships emphasize data analysis and insights. Your choice depends on whether you want to specialize in machine learning techniques or broader data analysis tasks.

What are the key skills and qualifications needed to thrive as a machine learning intern OPT CPT?

To thrive as a Machine Learning Intern (OPT CPT), you need a solid background in computer science, mathematics, and statistics, often demonstrated by coursework or a related degree. Experience with programming languages like Python or R, familiarity with machine learning frameworks such as TensorFlow or scikit-learn, and understanding of data analysis tools are commonly required. Strong problem-solving abilities, curiosity, and effective teamwork and communication skills help interns stand out. These skills are crucial for successfully contributing to projects, learning from real-world data, and collaborating with multidisciplinary teams.
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Machine Learning Internship Opt Cpt jobs near you

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX

Full-time

Posted 16 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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