Lead Robotics Software Engineer, Behavior Planning

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

The Lead Robotics SWE, Behavior Planning defines the technical strategy and architectural backbone that turns mission intent into safe, legible sidewalk motion. This position sets the contracts between mission, mapping, perception, prediction, planning, control, and tele-ops to ensure the system behaves consistently under real-world uncertainty. This role is the technical owner for reliability and observability at this layer, deciding what gets measured, how it’s validated, and when it’s ready to ship. Beyond writing excellent code, the Lead Robotics SWE, Behavior Planning mentors engineers, aligns stakeholders across autonomy and operations, and ensures robots meet policy and compliance expectations as the business expands to new cities.

Responsibilities

• Design and implement advanced behavior planning and control for autonomous sidewalk robots in complex urban environments.
• Architect mission/route ingestion at the robot level and integrate it with mapping, perception, prediction, planning, and control.
• Build and own the behavior layer (state machine/behavior tree) for cruise, overtake, peek/yield, and stop/move-to-side behaviors.
• Define lane selection and speed governance (right/center/road-side) with safety envelopes, comfort limits, and social etiquette.
• Instrument the stack with structured telemetry (option costs, clearances, interventions) and define KPIs and dashboards for release gating.
• 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.

Qualifications

• Phd/Master’s degree in Robotics, AI, Computer Science, Mathematics, or a related field.
• 7+ years of experience in a Robotics or AI related engineering role
• Strong foundation in behavior planning methods, including state machines, behavior trees, policy learning, and probabilistic planning.
• Proficiency in C++14/17 and Python; solid systems skills (concurrency, memory, performance).
• Proven experience debugging and resolving long-tail edge cases in real-world autonomous systems through targeted behavior planning strategies.
• 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.

What Makes You Stand Out

• 3+ years technical leadership/architecture experience
• Hands-on experience with motion planning and control algorithms for autonomous mobile robots.
• Background in integrating learning based motion planners with traditional planning pipelines for adaptive, real-time behavior.
• Experience with social navigation policies, occlusion reasoning, probabilistic prediction, and risk-aware planning.
• Proven ability to design and scale simulation environments using tools like NVIDIA Isaac Sim for development and validation of onboard autonomy.
• Experience with modern software development workflows, including the Bazel build system and CI/CD pipelines for deploying production-grade autonomy stacks.
• Please note: The base salary range listed in this job description reflects compensation for candidates based in the San Francisco Bay Area. While we prefer candidates located in the Bay Area, we are also open to qualified talent working remotely across the:

United States - Base salary range (U.S. – all locations): $190k - $230k USD

Canada - Base salary range (Canada - all locations): $160k - $190k CAD