Serve Robotics is looking for a Lead Software Engineer, Navigation and Behavior Planning to lead the development of advanced planning technologies for semi-structured urban environments. You will design and implement state-of-the-art algorithms for autonomous sidewalk robots to navigate complex scenarios with precision and safety.
What You'll Do
- Design and implement advanced planning and control algorithms for autonomous sidewalk robots operating in complex urban environments.
- Collaborate cross-functionally with mapping, perception, and sensor fusion teams to build robust dynamic agent prediction models, and tightly integrate them into the planning pipeline.
- Develop a semantic navigation stack that couples planning algorithms with rich semantic understanding from multi-modal sensor inputs.
- Drive improvements to the robot’s ability to handle failure scenarios, correct inefficiencies, and compose low-level robotic skills into high-level, goal-directed behaviors.
- Lead testing and validation efforts in both simulation and real-world deployments, ensuring planning systems are reliable, safe, and performant.
- Maintain clear and comprehensive documentation of algorithms, codebases, interfaces, and system designs to support cross-team collaboration and long-term maintainability.
What We're Looking For
- Master’s degree and 5+ years of experience in Robotics, AI, Computer Science, Mathematics, or a related field.
- Strong foundation in behavior planning methods, including state machines, behavior trees, policy learning, and probabilistic planning.
- Proven experience debugging and resolving long-tail edge cases in real-world autonomous systems through targeted behavior planning strategies.
- Working knowledge of machine learning techniques, particularly as applied to dynamic agent prediction and planning.
- Proficient in writing efficient, scalable, and robust code in C++ and Python.
- Excellent written and verbal communication skills, with the ability to articulate technical concepts clearly across teams.
Nice to Have
- PhD and 7+ years of experience in Robotics, AI, Computer Science, Mathematics, or a related field.
- Hands-on experience with motion planning and control algorithms for autonomous mobile robots.
- Familiarity with reinforcement learning techniques for planning and control, including imitation learning and policy optimization.
- Background in integrating learning based motion planners with traditional planning pipelines for adaptive, real-time behavior.
- Proven ability to design and scale simulation environments using tools like Gazebo and NVIDIA Isaac Sim for development and validation of planning systems.
- Experience with modern software development workflows, including the Bazel build system and CI/CD pipelines for deploying production-grade autonomy stacks.
Technical Stack
- C++
- Python
- Gazebo
- NVIDIA Isaac Sim
- Bazel
Team & Environment
You will join an agile, diverse, and driven team that solves complicated dynamic problems collaboratively and respectfully.
