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Reinforcement Learning Robotics Jobs in Missouri

VinMotion

AI Motion Intern - VinMotion US

California, MO · On-site

$100 - $125/hr

This role focuses on designing and implementing Reinforcement Learning (RL), Whole‑Body Control (WBC), Optimal Control, and AI‑powered Motion Planning techniques to enhance robotic agility ...

Slope

Staff AI Infrastructure Engineer

California, MO · On-site

$250/hr

ABOUT THE TEAM The Air Dominance & Strike team at Anduril develops aerial and multi-domain robotic ... reinforcement learning alignment loops (RLHF/DPO) to guarantee model safety and predictability in ...

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Reinforcement Learning Robotics information

What is reinforcement learning in robotics?

Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.

What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?

One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.

What are the key skills and qualifications needed to thrive as a reinforcement learning robotics engineer, and why are they important?

To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.

What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?

AspectReinforcement Learning RoboticsMachine Learning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; knowledge of reinforcement learningDegree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms
Work EnvironmentRobotics labs, manufacturing, autonomous systemsTech companies, data-driven projects, software development
Industry UsageAutonomous robots, industrial automation, researchData analysis, predictive modeling, AI applications

Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.

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Reinforcement Learning Robotics jobs near you

Sr. Robotics Engineer

California, MO • On-site

well-funded deeptech startup
See more jobs at well-funded deeptech startupexternal

$150 - $200/hr

Other

Posted 22 days ago

Job description

Sr. Robotics Engineer – AI-Powered Robotics Startup – $180-200k base + equity

You Will
  • Develop autonomous behaviors and algorithms for next-generation industrial robotic systems
  • Develop and model motion paths and obstacle avoidance strategies for multiple robotic arms in a highly cluttered workspace
  • Optimize control approaches for smooth handling and minimum latency
  • Work with custom tools including end effectors and other robotic mechanisms
  • Design and write production-quality C++ code
You Have
  • BS in Computer Science, Robotics, or a related field
  • Strong proficiency in C++ and Python
  • 5+ years of experience writing production code in C++
  • Familiarity with planning and control algorithms applied to deployed robotics or self-driving vehicles
  • Experience with ROS
  • Willingness to learn and work in a variety of technical areas outside your comfort zone
  • Ability to multi-task multiple projects in a fast-paced startup environment
Bonus If You Have
  • MS or Ph.D. in Computer Science, Robotics, or a related field
  • Experience working with industrial robot systems including robotic arms, cameras, and grippers
  • Experience using ROS2 as middleware
  • Experience with autonomous behavior abstractions such as behavior trees
  • Experience developing low-level controller code
  • Familiarity with reinforcement learning, machine learning or computer vision
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