Why RoboForceRoboForce is an AI robotics company developing Physical AI-powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.
We are seeking a
Senior Robotics Engineer, Navigation & SLAM to own the mobility stack for our fleet. In this role, you will enable robust autonomy in environments where standard 2D navigation breaks down-architecting state estimation systems that operate reliably in GPS-denied zones and building traversability analysis pipelines that determine whether terrain is safe to cross. You are not just solving point-to-point navigation; you are solving the physics of mobility on unpredictable terrain.
Responsibilities - Robust State Estimation: Architect and implement high-fidelity localization systems that fuse multi-modal sensor data, including LiDAR, visual odometry, IMU, and proprioceptive signals. You will build and maintain Kalman Filter or Factor Graph backends that achieve reliable accuracy under vibration, low-texture conditions, sensor occlusion, and dynamic environments.
- 3D Traversability Analysis: Convert raw sensor data into actionable navigation representations. You will develop real-time algorithms to analyze terrain geometry-estimating slope, roughness, step height, and clearance-to determine whether a path is safe given the robot's mobility constraints.
- Kinematically Constrained Planning: Design global and local planners that respect the physical limits of the platform, including non-holonomic constraints, stability margins on slopes, and traction limits on soft or uneven ground. Your planners must generate trajectories that are dynamically feasible, safe, and robust.
Requirements - Experience: Ph.D. in Robotics, Mechanical Engineering, Computer Science, or a related field, OR an M.S. degree with 4+ years of relevant industry experience.
- Probabilistic Robotics: Deep understanding of state estimation theory, including Kalman Filters and/or Factor Graphs. You are comfortable modeling sensor noise, uncertainty, and covariance in non-ideal conditions.
- SLAM Expertise: Proven experience building, deploying, or maintaining SLAM systems on real robotic platforms.
- 3D Navigation: Strong grasp of path planning in 3D environments, including costmap generation from point clouds and the use of sampling-based or optimization-based planners.
- C++ Performance Engineering: Expertise in modern C++ (C++17/20), with strong attention to real-time performance, memory management, and efficient processing of high-bandwidth sensor streams.
- Requires 5 days/week in-office collaboration with the teams.
Bonus Qualifications- GNSS / RTK Fusion: Experience integrating GPS or RTK receivers into localization stacks for global positioning in outdoor environments.
- Slip & Traction Estimation: Background in detecting slip or loss of traction from sensor signals and adapting planning or control constraints accordingly.
- GPU Acceleration: Experience using CUDA to accelerate perception, grid generation, or navigation pipelines.
Benefits- Competitive stock options/equity programs.
- Health, dental, and vision insurance, 401(k) plan.
- Visa sponsorship and green card support for qualified candidates.
- Lunches and dinners, a fully stocked kitchen, and regular team-building events.
