ZipRecruiter

Log In

1

Reinforcement Learning Internship Jobs in Texas (NOW HIRING)

Waabi

Research Scientist, Learnable Planner

Dallas, TX · On-site +1

$158K - $269K/yr

... reinforcement learning, optimal control, optimization based approaches, search methods, probabilistic decision making). - Demonstrated research experience through previous internships, work ...

Waabi

Research Scientist, Learnable Planner

Dallas, TX · On-site +1

$158K - $269K/yr

... reinforcement learning, optimal control, optimization based approaches, search methods, probabilistic decision making). - Demonstrated research experience through previous internships, work ...

Waabi

Research Scientist, Simulation Agents

Dallas, TX · On-site +1

$158K - $269K/yr

... reinforcement learning, generative models, foundation models, planning and search, and other ... Mentor junior scientists and interns; foster a culture of scientific rigor and rapid ...

Waabi

Research Scientist, Learnable Planner

Dallas, TX · On-site +1

$158K - $269K/yr

... reinforcement learning, optimal control, optimization based approaches, search methods, probabilistic decision making). - Demonstrated research experience through previous internships, work ...

Waabi

Research Scientist, Simulation Agents

Dallas, TX · On-site +1

$158K - $269K/yr

... reinforcement learning, generative models, foundation models, planning and search, and other ... Mentor junior scientists and interns; foster a culture of scientific rigor and rapid ...

Waabi

Research Scientist, Simulation Agents

Dallas, TX · On-site +1

$158K - $269K/yr

... reinforcement learning, generative models, foundation models, planning and search, and other ... Mentor junior scientists and interns; foster a culture of scientific rigor and rapid ...

Apple

Hardware Systems Engineering

Austin, TX

$122K - $161K/yr

... and reinforcement learning, as well as other related areas such as accessibility, privacy, and ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

Apple

Hardware Systems Engineering

Austin, TX

$122K - $161K/yr

... and reinforcement learning, as well as other related areas such as accessibility, privacy, and ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

Apple

Hardware Systems Engineering

Austin, TX · On-site

$122K - $161K/yr

... and reinforcement learning, as well as other related areas such as accessibility, privacy, and ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

Apple

Hardware Systems Engineering

Austin, TX

$122K - $161K/yr

... and reinforcement learning, as well as other related areas such as accessibility, privacy, and ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

next page

Showing results 1-20

All JobsReinforcement Learning JobsReinforcement Learning Internship JobsReinforcement Learning Internship Jobs in Texas

Reinforcement Learning Internship information

What are some common challenges faced during a Reinforcement Learning Internship and how can I prepare for them?

As a Reinforcement Learning Intern, you may encounter challenges such as tuning hyperparameters, managing computational resources, and understanding the intricacies of reward design. Interns often work with large datasets and complex environments, which can be resource-intensive and require efficient coding skills. To prepare, it's helpful to familiarize yourself with popular RL frameworks (like TensorFlow or PyTorch), brush up on mathematical concepts such as Markov Decision Processes, and practice implementing algorithms from academic papers. Collaboration with senior researchers and regular code reviews are also key aspects of the internship experience.

What is a Reinforcement Learning Internship?

A Reinforcement Learning Internship is a temporary position, often for students or recent graduates, where you work on projects involving reinforcement learning—a type of machine learning where agents learn by interacting with their environment to achieve goals. Interns typically assist with research, data analysis, algorithm development, and experimentation under the supervision of experienced professionals. This role provides hands-on experience with RL frameworks, coding in languages like Python, and exposure to real-world applications such as robotics, gaming, or autonomous systems. The internship helps build practical skills and can pave the way for advanced study or a career in artificial intelligence research.

What are the key skills and qualifications needed to thrive as a Reinforcement Learning Intern, and why are they important?

To thrive as a Reinforcement Learning Intern, you need a strong background in mathematics (especially probability, statistics, and linear algebra), programming proficiency (commonly in Python), and foundational knowledge of machine learning concepts. Experience with libraries and frameworks such as TensorFlow, PyTorch, OpenAI Gym, and familiarity with relevant research papers or coursework are highly beneficial. Analytical thinking, creativity, and effective communication skills help interns solve complex problems and collaborate with research teams. These skills are crucial for contributing to innovative RL projects and efficiently learning from real-world experimentation.

What is the difference between Reinforcement Learning Internship vs Machine Learning Internship?

AspectReinforcement Learning InternshipMachine Learning Internship
Required SkillsReinforcement learning algorithms, Python, data analysisSupervised/unsupervised learning, Python, data preprocessing
Work EnvironmentResearch labs, AI startups, tech companiesTech firms, research institutions, data-driven companies
Industry UsageSpecialized in decision-making models and sequential learningBroader applications including classification, regression, clustering

Reinforcement Learning Internship focuses on decision-making algorithms and sequential learning, often in research or AI startup environments. Machine Learning Internship covers a wider range of algorithms and applications, suitable for various industries. Both roles require programming skills and a background in data science, but reinforcement learning internships are more specialized in AI decision systems.

What are the most commonly searched types of Reinforcement Learning jobs in Texas? The most popular types of Reinforcement Learning jobs in Texas are:
What are popular job titles related to Reinforcement Learning Internship jobs in Texas? For Reinforcement Learning Internship jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Internship jobs in Texas look for? The top searched job categories for Reinforcement Learning Internship jobs in Texas are:
What cities in Texas are hiring for Reinforcement Learning Internship jobs? Cities in Texas with the most Reinforcement Learning Internship job openings:
Reinforcement Learning Internship jobs near you
Infographic showing various Reinforcement Learning Internship job openings in Texas as of July 2026, with employment types broken down into 2% Internship, 76% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.
Data Science Machine Learning Internship (Summer 2027)

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX

Full-time

Posted 6 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