Autonomy Engineer

Nextpower•Fremont, CA

1d•$160,000 - $190,000

About The Position

About Nextpower Nextpower is a global leader in intelligent solar tracker and software solutions, optimizing solar power plant performance worldwide. Within Nextpower, the Robotics and Autonomy team is building and deploying robotic systems that operate at scale in real solar environments. These systems combine perception, planning, control, embedded compute, and cloud infrastructure to increase inspection capacity, improve safety, and enable scalable operations. We are seeking a Autonomy Engineer to help accelerate the next phase of that growth. This role focuses on advancing real-world autonomy performance across the navigation stack and enabling robots to operate more independently, more efficiently, and at greater scale. This is a systems-level role spanning perception, planning, and control. You will work directly on robots, in the field and in test environments, to ensure the system performs reliably under real-world conditions. Role Overview We are scaling both the capability and deployment of our robotic systems. As autonomy improves, the system must support more robots per operator, operate with higher levels of autonomy across diverse environments, and maintain consistent performance as complexity increases. This role is focused on building and improving a tightly integrated autonomy stack that works end-to-end on the robot. You will operate within constrained embedded systems where compute, bandwidth, and power are limited, requiring thoughtful tradeoffs in model selection, algorithm design, and system architecture. You will design and implement perception, planning, and control systems, validate them on real hardware, and continuously improve performance through testing, simulation, and data-driven iteration. You are expected to own system behavior, not just individual algorithms. This means understanding how the full stack behaves in real environments, identifying gaps, and driving improvements that make the system more capable, reliable, and scalable. Core areas of responsibility include: Developing and improving autonomy capabilities across perception, planning, and control Getting systems working on real robots, not just in simulation Debugging and resolving issues observed in real-world operation Building and using simulation, log replay, and data pipelines to accelerate iteration Collaborating across hardware, integration, and test teams to ensure system-level performance

Requirements

Bachelor’s degree in Robotics, Computer Science, Electrical Engineering, or related field
5+ years of experience in robotics, autonomy, or related fields, with demonstrated experience developing software for robotic or autonomous systems in real-world environments (not just simulation)
Strong proficiency in at least one of the following: C, C++, Python, or Rust
Strong experience with Linux command-line environments, Git, and Docker
Strong experience with ROS2-based systems
Strong problem-solving skills and ability to debug complex system behavior
Strong hands-on experience working with physical robotic systems
Coachable and able to operate effectively within a fast-moving, collaborative team

Nice To Haves

Developing and deploying perception systems such as: Terrain classification Object detection, recognition, and tracking Semantic understanding of environments Model training, evaluation, deployment, and inference optimization on constrained embedded systems (e.g., CUDA, TensorRT, ONNX Runtime)
Designing and implementing robot control and planning systems, including: Low-level path control (e.g., Model Predictive Control (MPC)) Path planning algorithms such as A, Dijkstra’s algorithm, or similar Multi-robot planning or coordination
Building sensor fusion, filtering, localization, and/or state estimation algorithms, such as: Kalman Filters, Extended Kalman Filters (EKF) Graph-based optimization methods Characterizing sensor and motion noise
Working with simulation tools such as Gazebo or similar
Using log replay, data pipelines, and performance visualization to debug and improve systems
Applying CI/CD, release processes, and test-driven development in robotics systems
Debugging networking, remote systems, or communication stacks in deployed environments
Operating and deploying systems in outdoor, field robotics environments, including working under compute, bandwidth, and latency constraints

Responsibilities

Developing and improving autonomy capabilities across perception, planning, and control
Getting systems working on real robots, not just in simulation
Debugging and resolving issues observed in real-world operation
Building and using simulation, log replay, and data pipelines to accelerate iteration
Collaborating across hardware, integration, and test teams to ensure system-level performance