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Internship Deep Reinforcement Learning Jobs (NOW HIRING)

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving ... This engineer will leverage their deep expertise in RL to solve critical locomotion and ...

MLabs

Reinforcement Learning Engineer

New York, NY · On-site

$87K - $118K/yr

Reinforcement Learning (RL) Engineer Location: New York (Office) On-site | Full-time Compensation ... A deep-dive assessment into RL architecture, simulation frameworks, and live production experience.

MLabs

Reinforcement Learning Engineer

New York, NY

$87K - $118K/yr

Reinforcement Learning (RL) Engineer Location: New York (Office) On-site | Full-time Compensation ... A deep-dive assessment into RL architecture, simulation frameworks, and live production experience.

poolside

Member of Engineering (Reinforcement Learning)

$99K - $136K/yr

What unites us is our deep care for what we build together. We're in a race that requires hard work ... ABOUT THE ROLE You would be working on our reinforcement learning team focused on improving ...

Boston Dynamics

Staff, ML Research Scientist

Waltham, MA · On-site

$154K - $192K/yr

Experience in the full modeling cycle from research to deployment of modern Deep Learning architectures such as Transformers, VLMs/VLAs, and Deep Reinforcement Learning. * Knowledge of ...

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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.

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Internship Deep Reinforcement Learning jobs near you
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.

Research Internship - Reinforcement Learning for Large Foundation Models

Tencent

Bellevue, WA

$80K - $124K/yr

Full-time

Medical

Posted 24 days ago

Job description

Business UnitWhat the Role EntailsAbout Tencent AI Lab at Seattle Area
Tencent is a leading internet company in China. Tencent AI Lab at Seattle Area was established in May 2017. The lab strives to continuously improve AI's capability in perception, cognition, and creativity. Researchers there aim at solving challenging real-world problems with advanced technologies and publish extensively at top conferences and journals.
Research Internship - Reinforcement Learning for Large Foundation Models

Tencent AI Lab is dedicated to advancing cutting-edge AI technologies, with a particular focus on innovative breakthroughs in large foundation models. The lab's long-term ambition is to drive the development of Artificial General Intelligence (AGI), and ultimately, Artificial Superintelligence (ASI). We are currently seeking research interns for the year of 2026, in the area of reinforcement learning (RL) for large foundation models, with an emphasis on developing stable and efficient RL algorithms. The goal is to empower large foundation models in complex reasoning ang agent tasks and enhance their capabilities in autonomous exploration and continuous learning. Our Seattle area office is located in Bellevue WA.

Every research intern will work with researchers on a research project aimed at attacking one of the core problems on the design and optimization of RL algorithms for large foundation models. Research areas include but are not limited to Reinforcement Learning Algorithms, Reward Modeling, and World Models. We will conduct large-scale experiments of RL algorithms in scenarios such as complex reasoning and autonomous agents, deliver impactful algorithms for real world applications, and publish influential research papers.

Who We Look For
Requirements & Qualifications

The ideal intern candidates are those who

  • Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields from a top university,
  • are self-motivated and excited about developing novel techniques,
  • have research experiences in natural language processing or machine learning,
  • are proficient in Python programming and experienced in developing with deep learning frameworks such as PyTorch.
  • have good publication track records and history of creativity and intellectual flexibility,
  • have excellent communication and teamwork skills, capable of collaborating with cross-functional teams to drive project success and innovation.
  • Intern duration: 3 months (with the possibility of extension). Can start any time in the year 2026.

Location State(s)

US-Washington-BellevueThe expected base pay range for this position in the location(s) listed above is $80,168.40 to $124,800.00 per year. Actual pay may vary depending on job-related knowledge, skills, and experience. This position will be eligible for 1 hour of paid sick leave for every 30 hours worked and up to 13 paid holidays throughout the calendar year. Subject to the terms and conditions of the applicable plans then in effect, full-time interns are also eligible to enroll in the Company-sponsored medical plan.Equal Employment Opportunity at Tencent

As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.

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