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Deep Reinforcement Learning information

What does a typical day look like for someone working in Deep Reinforcement Learning?

A typical day for a Deep Reinforcement Learning professional involves designing algorithms, running experiments, analyzing results, and optimizing models to improve performance. You may collaborate regularly with data scientists, software engineers, and domain experts to integrate RL solutions into larger systems or products. Tasks often include reading the latest research, contributing to code reviews, and documenting findings while troubleshooting technical challenges. This dynamic environment encourages continuous learning and teamwork, ensuring you stay at the forefront of AI innovation.

What is a Deep Reinforcement Learning job?

A Deep Reinforcement Learning (DRL) job involves researching, developing, and applying AI models that use reinforcement learning techniques combined with deep learning. Professionals in this role design algorithms that enable agents to learn optimal decision-making policies through trial and error. Common applications include robotics, game AI, autonomous systems, and financial modeling. This job typically requires expertise in machine learning, neural networks, and programming languages like Python, along with frameworks such as TensorFlow or PyTorch.

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

To thrive in Deep Reinforcement Learning, you need expertise in machine learning, programming (Python, TensorFlow, or PyTorch), and applied mathematics, often supported by an advanced degree in computer science or a related field. Familiarity with version control systems, cloud computing platforms, and relevant certifications in AI or data science are valuable assets. Strong problem-solving abilities, collaboration, and effective communication are important soft skills in this position. These skills are essential for developing, implementing, and iterating cutting-edge algorithms that solve complex real-world problems in dynamic environments.

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:
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Deep Reinforcement Learning jobs near you
Reinforcement Learning Planning Research Intern

Reinforcement Learning Planning Research Intern

PlusAI

Santa Clara, CA • On-site

$19 - $65/hr

Other

Retirement

Re-posted 22 days ago

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World's Most Innovative Companies. Partners including TRATON GROUP's Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you're ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

Autonomous vehicles (AVs) need to navigate complex environments not just smoothly, but with absolute safety. While traditional planners handle standard driving behavior, edge-case scenarios and sudden environmental changes require an unyielding safety net.

This summer, you will own the development of a Safety-Critical Trajectory Correction (STC) module. Acting as a real-time safety overlay, the STC will function as a fallback mechanism that intercepts and minimally perturbs intended trajectories when collision risks are detected. You will design, train, and validate this architecture using Deep Reinforcement Learning to provide a continuous, constrained safety barrier for our vehicle fleet.
Responsibilities
  • Conduct groundbreaking research with the potential to strongly impact Plus's autonomous driving products, leading to publishable results. Key focus area for this internship will be reinforcement learning to generate safe trajectories for autonomous driving.
  • Develop and benchmark cutting-edge techniques in deep learning. 
  • Collaborate with team members to optimize and seamlessly integrate developed techniques into the production perception/AV stack.
Required Skills:
  • Pursuing MS or PhD in CS, EE, mathematics, statistics or related field
  • Thorough understanding of reinforcement learning
  • 1-2 years experience with implementing and training models in at least one deep learning framework (PyTorch, Tensorflow, Jax
Preferred Skills:
  • Past experiences in design, implementation and training of deep reinforcement learning models
  • Past experiences in projects related to autonomous driving 
$19 - $65 an hour
Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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