Rl Engineer, End-To-End Autonomy

• Design and implement state-of-the-art online and offline reinforcement learning algorithms for complex tasks with long horizons
• Formulate reward models and exploration strategies that enable task performance and adherence to strict safety requirements
• Enable flexible customer operation across a range of tasks with natural language instructions
• Enhance policy robustness to challenges such as sensor noise, machine wear, and extreme environmental variability
• Design and conduct experiments
• develop evaluation frameworks for simulation and real-world deployment
• Collaborate closely with infrastructure engineers to design scalable E2E training systems, including large-scale simulation infrastructure
• Collaborate with pretraining and robotics engineers to integrate RL seamlessly into the full E2E autonomy stack
• Drive the E2E vision and act as an ambassador for an E2E-first organization
• Technical leadership and mentorship: serve as an in-house RL expert, elevating the team through code reviews, algorithmic guidance, and fostering a culture of rigorous scientific experimentation
• Stay up to date with the latest RL research and integrate advancements into our stack

• Proven track record in developing RL models. Prefer experience deploying to production for robotics and boosting key metrics
• Expertise in developing simulation environments and tackling the sim-to-real transfer
• Expertise in designing and developing software for complex systems
• Comfortable working on new hardware systems and working on new RL/ML/software problems
• Strong Python coding skills and proficiency with deep learning frameworks like PyTorch
• Comfortable working across traditional team boundaries to deliver results
• Excellent brainstorming, creative thinking, mathematical analysis, and communication skills
• Track record of regularly anticipating technical issues and making architectural and design decisions to avoid them
• BS/MS/PhD in CS or related field, and 3+ years delivering high-performance RL products professionally

• Experience with robotics middleware such as ROS or other robotics-focused software packages
• Strong CUDA background or other GPU frameworks
• Experience in multidisciplinary environments
• Have worked on embedded systems
• Experience with system architecture

Eligibility for Blue River’s bonus and benefit programs