Blue River Technology jobs

Blue River, a John Deere subsidiary, is hiring an RL Engineer to develop end-to-end machine learning and robotics solutions for autonomous agricultural and construction machinery. You'll design and implement reinforcement learning algorithms for complex robotic tasks, build scalable training systems, and collaborate across infrastructure, pretraining, and robotics teams to integrate RL into the full autonomy stack. The role requires 3+ years of professional RL experience with a proven track record in production robotics, strong Python and PyTorch skills, expertise in simulation and sim-to-real transfer, and a CS or related degree. This is a full-time position in Santa Clara with 3 days in-office expectation, offering $192k–$378k base salary plus bonus and benefits, with visa sponsorship available. The team is lean and moving quickly, so you should thrive with ambiguity and cross-functional collaboration; prior robotics middleware (ROS) or CUDA experience is a plus.

Blue River, a John Deere subsidiary, is building autonomous machinery for agriculture, construction, and forestry using computer vision and robotics. This ML Engineer role sits on the lean End-to-End (E2E) machine learning team and focuses on designing and implementing production ML systems for complex navigation and manipulation tasks, including policy development, data pipeline management, edge deployment, and safety validation. You'll need proven experience shipping ML models to production for robotics systems, strong Python and PyTorch skills, and comfort working across hardware, robotics, and infrastructure engineering teams; experience with ROS, CUDA, embedded systems, or system architecture is preferred. The position is based in Santa Clara, CA with 3 days in-office weekly, offers visa sponsorship, and carries a US salary range of $135K–$378K plus bonus eligibility. A standout detail: this role emphasizes technical leadership and mentorship to shape the organization's E2E-first culture, while also requiring hands-on work across the full ML lifecycle from data collection through field validation.