Principal Motion Planning Engineer

Get to Know the Team

Our team develops production-grade robotics and autonomy capabilities for the uniquely complex unstructured urban environments of Southeast Asia. We are ambitious and pragmatic: advancing perception planning and control step by step with safety evidence as the gate for every milestone. We focus on building robust system capabilities scaling with uncompromised quality and collaborating with industry leaders while investing in in-house expertise where it differentiates us.

We are a senior hands-on engineering group that prizes operational excellence clear interfaces and reproducible pipelines.

Get to Know the Role

As the Principal Motion Planning Engineer you will own the behavioral and motion planning stack for Grabs autonomous platform.

You will architect deliver and continuously improve a production-grade motion planning system that integrates constrained trajectory optimization with learning-based models for interaction-aware decision-making in complex urban environments.

You will lead closed-loop validation and ML experimentation across simulation and real-world testing to measurably improve planner robustness safety and performance.

This is a hands-on technical leadership role with domain ownership of planning. You will report to the Head of Engineering.

The Critical Tasks You Will Perform

Technical Direction & System Architecture

• Define and evolve the technical direction for the motion planning stack spanning behavioural planning and trajectory generation.
• Architect a scalable production-grade planning stack tailored to the challenges of Southeast Asian environments.
• Ensure coherent integration of planning with upstream perception/prediction signals and downstream execution layers balancing architectural clarity with system performance.
• Lead technical design reviews within the planning domain ensuring robustness safety alignment and production readiness.

Hands-on Development & Implementation

• Lead the development of real-time motion planning algorithms including behaviour selection constrained trajectory optimization and interaction-aware decision-making.
• Design integrate and evaluate learning-based planning components in real-time systems ensuring measurable improvements in closed-loop performance.
• Drive data-driven experimentation using logged and simulated data to improve planner behaviour and robustness.
• Lead the lifecycle of planning components: specification design implementation testing (simulation SIL/HIL) and deployment.

Cross-Functional Collaboration & Technical Influence

• Mentor engineers within the planning domain and improve for design rigor experimentation discipline and production readiness.
• Partner with Perception Prediction Mapping and Control to ensure coherent system behaviour and trajectory feasibility.
• Help build a culture of data-driven iteration and technical excellence across the autonomy stack.

Qualifications :

What Essential Skills You Will Need

Essential Skills

• 8 years of experience building motion planning systems for autonomous vehicles or complex robotics platforms.
• Experience designing and shipping production-grade planning systems operating in real-time safety-critical environments.
• Proficiency in modern C (C17) for performance-critical systems and Python for ML experimentation workflows.
• Expertise in trajectory generation constrained optimization and interaction-aware behavior planning.
• Demonstrated experience designing training and deploying learning-based planning components in real-time systems.
• Experience building data pipelines and experimentation frameworks to improve learned planner performance.
• Hands-on experience with closed-loop simulation scenario mining and performance benchmarking.
• Experience with vehicle dynamics constraints and trajectory feasibility.
• Experience operating within safety-oriented development practices.
• BS/MS/PhD in CS EE Robotics or equivalent practical experience.

Preferred Skills

• Experience with imitation learning reinforcement learning or cost-learning approaches applied to motion planning.
• Experience operating planning systems at fleet scale or in dense urban environments.
• Familiarity with large-scale simulation platforms and scenario-based evaluation frameworks.
• Experience with safety frameworks (e.g. ISO 26262 SOTIF) and evidence-driven readiness gates.
• Publications patents or open-source contributions in autonomy robotics or planning.

Additional Information :

Life at Grab

We care about your well-being at Grab here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through lifes challenges.
• Balancing personal commitments and lifes demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer we consider all candidates fairly and equally regardless of nationality ethnicity religion age gender identity sexual orientation family commitments physical and mental impairments or disabilities and other attributes that make them unique.

Remote Work :

No

Employment Type :

Full-time