Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

About the Team:

The Robotics Technology team is a core part of Grab's long-term vision to build urban embodied AI. Our engineers take full ownership of the product lifecycle: designing and manufacturing hardware in-house, developing control and machine‑learning systems, and rigorously testing in real-world conditions and production fleet operations. This is a fast-moving, multidisciplinary environment where software, hardware and data science experts collaborate to solve practical challenges at scale. We are executing an ambitious growth plan to expand our robotics fleet across cities over the coming years, and we are focused on delivering highly productive, safe and efficient robot delivery services that help address current delivery labor shortages.

Based in Singapore and China, we offer opportunities to work on the latest autonomy, deploy solutions in complex environments, and directly influence the future of last‑mile logistics. If you're excited by tangible impact, large-scale systems and cross-functional engineering, you'll find meaningful challenges and rapid career growth here.

You will report to the Head of Engineering.

Work type: 5-day in office at Grab Headquarter.

Get to know the Role:

As the core architect of "Spatial Intelligence" for our last-mile delivery robots, you will lead the R&D of high-precision, robust, and cost-effective SLAM technologies. Your work will directly determine the robot's ability to navigate autonomously and safely through complex, dynamic urban environments (e.g., residential areas, commercial streets, office parks), driving the system from prototype to large-scale commercial deployment.

Work Type: 5-day onsite.

The critical tasks you will perform

1. Core Algorithm R&D & Optimization (50%)

• Multi-modal Fusion: Lead the development of SLAM algorithms for large-scale, semi-structured environments, focusing on tightly-coupled localization and mapping architectures using LiDAR, Vision, Odometry, and IMU.
• Scenario Robustness: Overcome unique last-mile challenges: filtering dense dynamic obstacles, resolving localization ambiguity in repetitive scenes, ensuring seamless indoor-outdoor transitions, and maintaining stable centimeter-level localization in GNSS-denied areas (e.g., urban canyons, tunnels).
• Cost-Efficient Solutions: Build SLAM solutions optimized for low-cost hardware (e.g., solid-state LiDAR, cameras) and ensure long-term map stability.

2. Engineering Excellence & Deployment (30%)

• Performance Balancing: Lead the deployment and optimization of SLAM algorithms on edge platforms (e.g., NVIDIA Jetson Orin, Horizon J5), achieving an extreme balance between precision and high-frequency real-time output.
• Production Implementation: Refactor code architecture for production; manage memory, power consumption, and coordinate with hardware teams on sensor selection, calibration, and temporal synchronisation.
• Mapping Toolchain: Design and implement automated toolchains for map generation, updates, and cloud management to support rapid operational expansion.

3. Closed-loop Iteration & Collaboration (20%)

• Evaluation & Truth Systems: Build performance evaluation frameworks (using metrics like ATE and Loop Closure success rates) to drive continuous algorithm evolution via data loops.
• System Synergy: Collaborate with Perception and Planning/Control teams to provide high-quality, low-latency pose estimation and semantic map data, enhancing overall motion intelligence.

Qualifications

Skills you need

• Education: Master's degree or above in CS, Robotics, Automation, Geomatics, or related fields.
• Experience: 5+ years of SLAM R&D experience in robotics or autonomous driving; full-cycle experience in at least one mass-produced product.
• Technical Expertise: Proficient in at least two of the following:
• LiDAR SLAM: Mastery of LOAM series, LIO-SAM, and understanding of point cloud matching and Pose Graph optimization.
• Visual/Multi-sensor SLAM: Mastery of VINS, ORB-SLAM3, and proficiency in BA (Bundle Adjustment) and Factor Graph optimization.
• Large-scale Mapping: Experience in semantic SLAM, dynamic SLAM, or managing maps for large-scale urban scenes.
• Engineering Skills: Expert in high-performance C++; proficient in Linux/ROS 2; practical experience in SLAM acceleration using CUDA or TensorRT.
• Hybrid Fusion: Hands-on experience with tightly-coupled LIO-VIO systems.
• Navigation Stack: Familiarity with Nav2 or similar stacks and understanding how SLAM inputs affect path planning.
• Architectural Design: Ability in system architecture design, module refactoring, and performance bottleneck resolution.

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 life's challenges.
• Balancing personal commitments and life's 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.