Robotics Navigation and Control Engineer

About the company

The company is transforming freight logistics with autonomous robotic systems that load and unload trailers faster, safer, and more reliably than traditional methods. Our robots operate in demanding real-world environments alongside people and heavy cargo every day. We are a small, high-impact team based in Atlanta building products that are already deployed in production.

The Role

We are looking for a Robotics Navigation and Control Engineer to own the motion planning, path planning, and control systems on our autonomous mobile robots. Our robots navigate constrained spaces—inside trailers, across loading docks, and through active warehouse floors—carrying heavy loads with tight tolerances. This role is responsible for making that movement safe, precise, and reliable.

We need someone who has shipped navigation and controls software on real robots at real customer sites. You should have hands-on experience tuning controllers on physical hardware, dealing with wheel slip, load dynamics, and the gap between simulation and reality. Academic publications are great, but production deployment experience is what matters here.

Key Responsibilities

• Design, implement, and optimize path planning and trajectory generation for autonomous mobile robots operating in constrained logistics environments

• Develop and tune motion controllers (PID, MPC, or similar) for heavy-payload platforms with real-world dynamics

• Implement obstacle avoidance and safety behaviors that work reliably around people and infrastructure

• Own the localization stack, working with perception engineers to integrate sensor-based position estimates into the control loop

• Build simulation models and validate them against real robot behavior for faster development iteration

• Analyze and improve robot performance using field data, telemetry, and logs from deployed systems

• Collaborate with perception, hardware, and cloud infrastructure teams to deliver integrated autonomy features

• Contribute to CI/CD pipelines for controls software testing and deployment to the robot fleet

Requirements

• 5+ years of professional experience developing navigation and control systems for physical robots at a robotics or autonomous vehicle company

• Strong proficiency in C++ and Python

• Deep understanding of motion planning algorithms (A*, D*, RRT variants, lattice planners, or similar)

• Hands-on experience designing and tuning controllers for mobile robot platforms

• Production experience with ROS or ROS 2 navigation stacks

• Experience with localization techniques (EKF, particle filters, scan matching, visual odometry)

• Demonstrated ability to bridge the sim-to-real gap—tuning algorithms that work on actual hardware, not just in simulation

• Comfort analyzing system behavior from logs and telemetry data

• Strong communication skills and ability to work effectively in a small team

Nice to Have

• Master’s degree or higher in Robotics, Controls, Mechanical Engineering, or a related field

• Experience with model predictive control (MPC) or adaptive control approaches

• Experience with AWS IoT, Greengrass, or edge computing for fleet-scale robot management

• Familiarity with Gazebo, Isaac Sim, or other robotics simulation environments

• Background in logistics, warehousing, or heavy-payload robotics

Remote Work Requirements

This role can be filled remotely. Remote team members are expected to have reliable high-speed internet access and a dedicated workspace. You will need to travel to our Atlanta facility periodically for hardware integration, testing, and tuning on physical robots. A company laptop and necessary peripherals will be provided.

Benefits

What We Offer

• Competitive salary and equity in an early-stage robotics company

• Comprehensive benefits including health, dental, and vision

• Permissive time off policy

• A small team where your work has direct, visible impact on shipped products

• The chance to work on robots that are operating in production today—not a research project