Software Engineer, Decision & Planning Algorithm (Robotics)

About This Role

Develop decision and planning algorithms for Grab's full-scenario delivery robots in Singapore. This role involves end-to-end ownership of planning systems for complex urban and indoor environments.

Responsibilities

• Design global routing and decision & motion planning systems for safety and efficiency.
• Research full-scenario driving on public roads and semi-enclosed campuses.
• Improve nonlinear, multi-objective planning in unstructured indoor settings.
• Contribute to quantitative metrics and data closed-loop expansion.
• Contribute to data-driven, end-to-end planning R&D and scenario optimization.
• Debug issues in simulation and on-vehicle tests.

Requirements

• Master's degree+ in CS, AI, applied math, or related field.
• 3–5 years R&D experience in autonomy/robotics planning algorithms.
• Solid C++, proficient Python and Linux.
• Experience with ROS/ROS2 or Apollo/Autoware.
• Knowledge of classical decision and planning methods (e.g., Hybrid A*).
• Hands-on experience with joint lateral–longitudinal planning.
• 3+ years experience in decision/planning under game-theoretic settings.
• Familiarity with ML for planning (e.g., RL, imitation learning).