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Internship Deep Reinforcement Learning Jobs (NOW HIRING)

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How much do internship deep reinforcement learning jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for internship deep reinforcement learning in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during a Deep Reinforcement Learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in Deep Reinforcement Learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

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

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

More about Internship Deep Reinforcement Learning jobs
What cities are hiring for Internship Deep Reinforcement Learning jobs? Cities with the most Internship Deep Reinforcement Learning job openings:
What are the most commonly searched types of Deep Reinforcement Learning jobs? The most popular types of Deep Reinforcement Learning jobs are:
What states have the most Internship Deep Reinforcement Learning jobs? States with the most job openings for Internship Deep Reinforcement Learning jobs include:
Infographic showing various Internship Deep Reinforcement Learning job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 53% Full Time, 44% Part Time, 1% Temporary, and 1% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Senior Machine Learning Engineer - Deep & Reinforcement Learning

Kanak Elite Services Inc

Houston, TX • On-site

$99K - $137K/yr

Contractor

Posted 5 days ago


Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Senior Machine Learning Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Position           : Senior Machine Learning Engineer – Deep & Reinforcement Learning

Location          : Houston, TX Onsite

Duration         : Long term contract

Required skills:
- Degree in STEM field, Ph.D preferred.
- Master in Deep Learning, Reinforcement Learning, and multimodal large language model.
- Strong Pytorch or TensorFlow programming
- Machine Learning and Statistical Modelling - Mastery
- Exploratory Analysis
- Core Programming Skills & Languages
- AI Engineering Essentials
- DevOps and Agile
- Cloud deployment frameworks, infrastructure, and tooling