Design intelligent movement for robots that move freight. We’re building autonomous mobile robots that operate in real logistics environments—trailers, loading docks, and warehouse floors—and we need an engineer to lead the development of their navigation and control systems. This role is hands-on, from algorithm design to real-world tuning, with a focus on safety, precision, and reliability.
What You’ll Do
- Develop and refine path planning and trajectory generation systems for robots navigating tight, dynamic spaces
- Design and tune motion controllers for heavy-duty platforms, accounting for real-world dynamics and load variations
- Implement reliable obstacle avoidance and safety logic that operates safely around people and infrastructure
- Own the robot’s localization stack, integrating sensor data into the control loop with input from perception systems
- Build and validate simulation models that accurately reflect physical robot behavior to accelerate development
- Use field data, telemetry, and logs to diagnose issues and improve performance across the robot fleet
- Work closely with perception, hardware, and cloud teams to deliver fully integrated autonomy features
- Support CI/CD pipelines for automated testing and deployment of control software updates
What We’re Looking For
- At least 5 years of experience building navigation and control systems for physical robots in production environments
- Strong coding skills in C++ and Python, with a focus on real-time systems
- Deep knowledge of motion planning algorithms such as A*, D*, RRT variants, or lattice-based planners
- Proven experience tuning controllers like PID or MPC on actual robot platforms
- Familiarity with ROS or ROS 2 navigation stacks in deployed systems
- Experience with localization methods including EKF, particle filters, scan matching, or visual odometry
- Ability to close the sim-to-real gap—your code must work in the field, not just in simulation
- Skill in analyzing system behavior from logs and telemetry
- Clear communication and collaboration habits, especially in small, cross-functional teams
Nice to Have
- Advanced degree in Robotics, Controls, Mechanical Engineering, or a related field
- Experience with model predictive or adaptive control strategies
- Background with AWS IoT, Greengrass, or edge computing for managing robot fleets
- Familiarity with Gazebo, Isaac Sim, or similar simulation tools
- Exposure to logistics, warehousing, or heavy-payload robotics applications
Technology We Use
C++, Python, ROS, ROS 2, A*, D*, RRT, lattice planners, PID, MPC, EKF, particle filters, scan matching, visual odometry, Gazebo, Isaac Sim, AWS IoT, Greengrass
Work Environment
This is a hybrid role. You can work remotely with a reliable high-speed connection and dedicated workspace, but periodic travel to our Atlanta facility is required for hardware integration, testing, and system tuning. The team is small and focused—your work directly shapes the product.
Compensation & Benefits
- Competitive salary and equity in an early-stage robotics company
- Full health, dental, and vision coverage
- Flexible time off policy
- Direct impact on robots currently operating in production environments
- No research prototypes—everything you build will be used in real logistics operations
