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Internship Deep Reinforcement Learning Jobs in California

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Internship Deep Reinforcement Learning information

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.

What are the most commonly searched types of Deep Reinforcement Learning jobs in California?

The most popular types of Deep Reinforcement Learning jobs in California are:

What are popular job titles related to Internship Deep Reinforcement Learning jobs in California?

For Internship Deep Reinforcement Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Deep Reinforcement Learning jobs in California look for?

The top searched job categories for Internship Deep Reinforcement Learning jobs in California are:

What cities in California are hiring for Internship Deep Reinforcement Learning jobs?

Cities in California with the most Internship Deep Reinforcement Learning job openings:

Infographic showing various Internship Deep Reinforcement Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Deep Reinforcement Learning Engineer - Autonomous Driving

NVIDIA Corporation

Santa Clara, CA • On-site

$224 - $357/hr

Other

This job post has expired today. Applications are no longer accepted.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

7th of 247 rated software companies


Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. At NVIDIA, we are pushing the boundaries of what’s possible within self-driving vehicle technology by bringing to bear the power of Deep Reinforcement Learning (RL). As a world leader in AI and high-performance computing, NVIDIA provides an outstanding platform where innovative research meets real-world production. We are looking for a Reinforcement Learning Engineer to join our mission in building intelligent, safe, and efficient self-driving technology that will redefine transportation on a global scale. NVIDIA uses AI tools in its recruiting processes.

What you'll be doing:
  • Build and implement brand new Reinforcement Learning (RL) algorithms for autonomous vehicle decision-making and planning.
  • Develop and maintain scalable training pipelines and simulation environments for RL training.
  • Collaborate with perception, and planning teams to integrate RL models into the unified autonomous driving stack.
  • Benchmark RL model performance against imitation learning baselines in complex urban environments.
  • Optimize and deploy RL models to production-grade automotive hardware.
What we need to see:
  • BS or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or equivalent experience).
  • 12+ years of experieence in the related field.
  • Solid background in Reinforcement Learning, including policy gradient methods (PPO, GRPO), actor-critic architectures, on-policy and off-policy RL.
  • Proficiency in PyTorch or TensorFlow and real experience with RL-related algorithm.
  • Experience in C++ and Python development for real-time systems.
  • Strong analytical and problem-solving skills, with a track record of implementing and debugging complex RL systems.
Ways to stand out from the crowd:
  • Background in shipping autonomous driving features or embodied AI.
  • Experience with generative models (Flow Matching, Diffusion, or AR-based decoders) in the context of policy representation or trajectory modeling.
  • Experience with training policies on their own rollout distributions and handling the compounding error problems inherent in autonomous driving.
  • Experience working with large-scale data flywheels, including mining scenarios from fleet telemetry logs, auto-labeling pipelines, and automated performance tracking.
Compensation:

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits.

Application deadline:

Applications for this job will be accepted at least until August 31, 2026.

Equal Opportunity Employer

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

This posting is for an existing vacancy.

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US