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Freelance Deep Reinforcement Learning Jobs (NOW HIRING)

The role combines deep theoretical research with hands-on system development and experimentation ... Conduct research on reinforcement learning methods for multi-modal systems, including diffusion ...

... with deep reinforcement learning in any context (autonomous vehicles, robotics, or LLMs) • Experience working with data generated by human experts for model training • Financial services ...

The selected candidate will drive the design, development, and integration of innovative Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) capabilities into defense and mission ...

Deep reinforcement learning We are looking for self-motivated, top-notch researchers to join us! * Passion to conduct innovative and hands-on research on robotics; * A strong track record on ...

Applied Reinforcement Learning Engineer Location: Palo Alto, CA or Seattle, WA (Hybrid/Remote ... This role requires deep expertise in both classical RL methodologies and modern LLM-based agent ...

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

As of May 30, 2026, the average hourly pay for freelance deep reinforcement learning in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.
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Infographic showing various Freelance Deep Reinforcement Learning job openings in the United States as of May 2026, with employment types broken down into 11% Full Time, and 89% Part Time. Highlights an 33% Physical, and 67% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Reinforcement Learning Engineer, Whole Body Controls, Optimus

Reinforcement Learning Engineer, Whole Body Controls, Optimus

Tesla

Palo Alto, CA • On-site

$98.30K - $127.10K/yr

Full-time

Posted 18 days ago


Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers


Job description

Job Summary:
Tesla is focused on solving robust embodied intelligence through humanoid robots, and they are seeking a Reinforcement Learning Engineer to develop cutting-edge policy learning algorithms. The role involves creating end-to-end reinforcement-learning policies for whole-body movements and evaluating these policies in both simulation and real-world settings.
Responsibilities:
• Develop end-to-end reinforcement-learning policies for whole-body movements
• Design observations, actions, and rewards based on first principles and deep physics understanding
• Develop techniques to improve sim2real transfer, including classical modeling techniques
• Evaluate policies both in simulation and on hardware
• Ship production-quality policies to a fleet of bots
Qualifications:
Required:
• Experience writing production-quality python (including numpy and pytorch)
• Solid understanding of robotics fundamentals, including geometry, linear algebra, kinematics, dynamics, probability, and statistics
• Familiarity with Machine learning and Reinforcement Learning fundamentals OR strong background in optimization-based planning and control
• Experience working with robotic systems, ideally on legged robotic systems with high degrees of freedom
• Experience with sim2real techniques OR deep understanding of physics fundamentals
• Experience implementing control strategies including impedance control, adaptive control, force control, MPC on hardware preferred
Preferred:
• Experience implementing control strategies including impedance control, adaptive control, force control, MPC on hardware
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Tesla employees say

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Benefits

Hours and flexibility

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