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Internship Deep Reinforcement Learning Jobs (NOW HIRING)

Bostondynamics

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 Sep 11, 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 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 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 are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

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 September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Staff, ML Research Scientist

Waltham, MA • On-site

Bostondynamics
See more jobs at Bostondynamicsexternal

$154K - $192K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago

Job description

As a Staff ML Research Scientist on the Machine Learning Safety R&D Team, you will join a small cross-functional group developing machine learning models that will enable our robots to operate safely around people. Every day you will help research, design, and build innovative machine learning models and algorithms to run on our robots. Your work will pave the way for our Embodied AI.

In this role you will chart a path by combining the best of state of the art ML architectures with real-world safe robotics challenges, ultimately creating novel solutions to one of the most important problems in robotics. If you are creative, thrive in a small team environment, and passionate about using machine learning to further a world where humans and robots truly work together - come join us!

How you will make an impact:

  • Research and build novel model architectures which allow our robots to operate safely around people.

  • Research, build, validate, and deploy ML models to detect hazards, humans, and other environmental features.

  • Develop datasets, metrics, and validation plans for ML model research.

  • Work closely with a small team to design and prototype new deep learning based perception and behavior models which create safety features for our robots.

We are looking for:

  • 5+ years of experience applying Deep Learning (ML) to scalable real-world problems in computer vision or LLMs.

  • 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 state of the art work in related areas of computer vision, world models, and Deep Reinforcement Learning. Publications are a plus.

  • Experience with the full lifecycle of Deep Learning development, including network design, data management, training, evaluation, hyperparameter search, deployment/productionalization, and online validation.

  • Strong communication skills, including ability to author technical documentation and deliver presentations on technical topics.

  • History of working in small, interdisciplinary teams.

The base pay range for this position is between $154,310 to $192,887 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and a annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.

We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas for this position

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