DiDi Labs
Autonomous Driving
SoftwareEngineer–MapFusion&Planning
Neural analysis suggests this role is
optimal for Senior candidates.
“Software Engineer – Map Fusion & Planning at DiDi Labs. Skills: Map fusion, Motion planning, Autonomous vehicles, Deep learning. Architect data flow pipelines. Architect APIs for map fusion”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
B.S./M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or related field, 3+ years experience (Software Engineer), 5+ years experience (Senior Software Engineer), Expert proficiency in production-grade C++, Prototyping proficiency in Python, Robust foundational knowledge in path planning, Knowledge of kinematic/dynamic vehicle models, Deep understanding of robotics fundamentals, Solid understanding of middleware, Solid understanding of distributed software architectures
Nice to Have
Hands-on experience with numerical trajectory optimization, Hands-on experience with optimization solvers, Hands-on experience with HD map formats, Hands-on experience with end-to-end learning frameworks, Proven track record of exporting deep learning architectures via ONNX, Proven track record of deploying into C++ production environments, Proven track record of developing anomaly detection algorithms, Knowledge of real-time operating systems, Knowledge of deterministic software execution, Knowledge of safety-critical software design principles
What You'll Do.
Architect data flow pipelines
Architect APIs for map fusion
Architect APIs for real-time map vectorization
Architect APIs for behavior/motion planning
Design robust software frameworks
Deploy robust software frameworks
Integrate offline HD maps
Integrate online perception data
Create unified local environment model
Implement state-of-the-art networks
Optimize state-of-the-art networks
Design motion planning algorithms
Implement motion planning algorithms
Validate motion planning algorithms
Establish feedback loop
Own end-to-end deployment pipeline
Execute models in C++
Develop anomaly detection algorithms
Develop scene-change detection algorithms
Optimize system latency
Optimize CPU memory footprint
Optimize GPU memory footprint
Optimize multi-threaded execution
Full Job Description
About the Company DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet. About the Role We are seeking a Software Engineer / Senior Software Engineer to develop the next-generation map fusion and motion planning systems for our autonomous vehicles. In this role, you will bridge the gap between semantic HD maps, real-time sensor perception, and vehicle trajectory generation. You will design scalable software infrastructure, implement advanced geometric and deep learning frameworks, and develop the planning algorithms that enable our vehicles to navigate complex, dynamic environments safely and predictably. Responsibilities System Architecture: Architect the data flow pipelines and APIs for map fusion, real-time map vectorization, and behavior/motion planning modules. Algorithm Deployment: Design and deploy robust software frameworks that integrate offline High-Definition (HD) maps with online perception data to create a unified local environment model. Advanced Mapping Networks: Implement and optimize state-of-the-art networks utilizing DETR-style, query-based vector decoding in bird's-eye-view (BEV) for online map element generation. Motion Planning & Optimization: Design, implement, and validate core motion planning algorithms, establishing a tight feedback loop between vectorized map features, path generation, and trajectory optimization. Model Deployment Pipelines: Own the end-to-end deployment pipeline for
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