AI Engineer - Reinforcement Learning (Senior)

As a Senior AI Engineer at RIVR, you will lead the development of reinforcement learning and deep learning solutions for autonomous robot control, using both simulation and real-world data. You’ll work closely with vision and imitation-learning teams to push robust, deployment-ready algorithms on real hardware, while mentoring engineers and guiding product strategy. This role sits at the intersection of research and production, shaping how Intelligent Robotics enables scalable last-mile delivery. Your work will have a tangible impact on robot autonomy, manipulation, and real-world performance.

• Develop cutting-edge reinforcement learning algorithms for autonomous robot control
• Design, test, and refine algorithms for real-world locomotion, autonomy, and manipulation
• Collaborate with computer vision and imitation learning teams using simulated and real-world data
• Implement deployment-ready code optimized for robot hardware constraints
• Build, lead and mentor a software engineering team
• Provide expert guidance to product managers and executives for strategic decisions
• Create and maintain documentation, guidelines, and best practices for knowledge sharing

• Master’s degree or higher in Engineering, Robotics, or Machine Learning
• ≥5 years of industry or research experience (PhD applicable)
• Strong deep learning fundamentals and RL including MDPs, policy optimization, model-based vs. model-free, sim-to-real, etc.
• Robotics background with autonomy and/or manipulation
• Experience deploying neural networks on hardware platforms
• Production-level C++ coding skills
• Python for prototyping and training deep networks
• PhD in related fields or equivalent research experience (bonus)
• Publications at top-tier conferences (bonus)
• Experience in managing a software team (bonus)

• Leadership and mentorship
• Cross-functional collaboration
• Strategic thinking and communication with product leadership
• Reinforcement learning and deep learning
• Supervised and self-supervised learning
• MDPs, policy optimization, model-based vs. model-free RL