We are seeking a passionate Robotics Autonomy Team Lead to join our team and drive the development of cutting-edge autonomous robotic systems. We value experience from high-scale autonomy/ADAS teams and modern planning/control stacks.
Responsibilities – what you will be doing:
Design, implement, test, and deploy motion planning and navigation algorithms that drive vehicles safely and efficiently in unpredictable terrains, generating collision-free paths and dynamic maneuvers
Own the autonomy decision-making stack end-to-end, including behavior planning (BT/FSM), navigation, trajectory generation, obstacle avoidance, and the planning-to-control interface
Build modern, predictive, and optimization-based planning approaches (trajectory optimization, MPC/NMPC, constraints, cost functions) that balance safety, comfort, and efficiency
Consume structured world representations from perception (e.g., semantics, occupancy, tracks, map-light cues) and produce time-parameterized trajectories with explicit constraints and fallbacks
Implement risk-aware autonomy: uncertainty handling, confidence gating, conservative envelopes, and degraded-mode behaviors when perception or localization is weak
Leverage real-world data and simulation to continuously refine and optimize algorithms, ensuring stability and resilience in harsh conditions
Establish an evaluation loop: closed-loop simulation, scenario packs, regression gates tied to KPIs (TTC, near-miss, jerk, stop distance, intervention rate)
Work closely with perception, hardware, product, integration, and testing teams to build and validate the full autonomy stack in simulation and in the field
Lead and mentor the autonomy team, set technical direction and roadmap, and raise the engineering quality bar (reviews, testing, architecture, delivery)
Responsibilities – what you will be doing:
Design, implement, test, and deploy motion planning and navigation algorithms that drive vehicles safely and efficiently in unpredictable terrains, generating collision-free paths and dynamic maneuvers
Own the autonomy decision-making stack end-to-end, including behavior planning (BT/FSM), navigation, trajectory generation, obstacle avoidance, and the planning-to-control interface
Build modern, predictive, and optimization-based planning approaches (trajectory optimization, MPC/NMPC, constraints, cost functions) that balance safety, comfort, and efficiency
Consume structured world representations from perception (e.g., semantics, occupancy, tracks, map-light cues) and produce time-parameterized trajectories with explicit constraints and fallbacks
Implement risk-aware autonomy: uncertainty handling, confidence gating, conservative envelopes, and degraded-mode behaviors when perception or localization is weak
Leverage real-world data and simulation to continuously refine and optimize algorithms, ensuring stability and resilience in harsh conditions
Establish an evaluation loop: closed-loop simulation, scenario packs, regression gates tied to KPIs (TTC, near-miss, jerk, stop distance, intervention rate)
Work closely with perception, hardware, product, integration, and testing teams to build and validate the full autonomy stack in simulation and in the field
Lead and mentor the autonomy team, set technical direction and roadmap, and raise the engineering quality bar (reviews, testing, architecture, delivery)
Requirements:
BSc/MSc in CS/EE/Robotics (or equivalent experience), with 6+ years building and deploying autonomy on real robotic/autonomous platforms
Strong understanding of motion planning and navigation (theory + practice)
Hands-on experience with modern planning + control, including trajectory optimization and/or MPC/NMPC
Proficient with production engineering practices (version control, code review, CI, testing, profiling)
Proven ability to lead SW/Algo engineers and guide technical direction
Experience building robustness under uncertainty: confidence-aware logic, risk-aware planning, and safe fallbacks
Advantages – Youll Stand Out If You Have
Experience deploying autonomy in off-road/agricultural/unstructured environments
Professional ROS2 (C++) experience
Experience using AI/ML inside autonomy (e.g., learned costmaps/traversability priors, learned heuristics, policy proposals), with deterministic safety guards
Background in high-scale autonomy/ADAS teams, bringing practices like scenario mining, sim-first validation, fleet triage, and metric-driven releases
Familiarity with occupancy/semantics / lane-less or map-light planning inputs in real-world systems
BSc/MSc in CS/EE/Robotics (or equivalent experience), with 6+ years building and deploying autonomy on real robotic/autonomous platforms
Strong understanding of motion planning and navigation (theory + practice)
Hands-on experience with modern planning + control, including trajectory optimization and/or MPC/NMPC
Proficient with production engineering practices (version control, code review, CI, testing, profiling)
Proven ability to lead SW/Algo engineers and guide technical direction
Experience building robustness under uncertainty: confidence-aware logic, risk-aware planning, and safe fallbacks
Advantages – Youll Stand Out If You Have
Experience deploying autonomy in off-road/agricultural/unstructured environments
Professional ROS2 (C++) experience
Experience using AI/ML inside autonomy (e.g., learned costmaps/traversability priors, learned heuristics, policy proposals), with deterministic safety guards
Background in high-scale autonomy/ADAS teams, bringing practices like scenario mining, sim-first validation, fleet triage, and metric-driven releases
Familiarity with occupancy/semantics / lane-less or map-light planning inputs in real-world systems
This position is open to all candidates.
