DiDi Labs

Software Engineer – Map Fusion & Planning

San Jose, CA

Sponsorship not specified$141k-$235kDetected 11 days ago

PythonC++AlgorithmsDeep LearningEmbedded SystemsRoboticsElectrical Engineering

About the role

In this role, you will bridge the gap between semantic HD maps, real-time sensor perception, and vehicle trajectory generation.

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.
Safety & Anomaly Detection: Develop real-time map anomaly and scene-change detection algorithms to ensure planning system reliability under varying or outdated map conditions.
Performance Optimization: Optimize system latency, CPU/GPU memory footprint, and multi-threaded execution of safety-critical C++ modules.
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.
Design, implement, and validate core motion planning algorithms, establishing a tight feedback loop between vectorized map features, path generation, and trajectory optimization.
Knowledge of real-time operating systems (RTOS), deterministic software execution, and safety-critical software design principles.

Software Mastery: Expert proficiency in production-grade C++ (Modern C++14/17/20, multi-threading, memory management) and strong prototyping proficiency in Python.
Expert proficiency in production-grade C++ (Modern C++14/17/20, multi-threading, memory management) and strong prototyping proficiency in Python.
Hands-on experience with numerical trajectory optimization methods (e.g., MPC, QP/Nonlinear optimization, interior-point methods) and optimization solvers (e.g., OSQP, Ipopt, Ceres Solver).
Education: B.S./M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field.
Motion Planning Fundamentals: Robust foundational knowledge in path planning (e.g., A*, Dijkstra, Hybrid A*, sampling-based planners like RRT*) and kinematic/dynamic vehicle models.
Robotics Core: Deep understanding of robotics fundamentals, including coordinate transformations, spatial geometry, and state estimation.
System Design: Strong system design skills with a solid understanding of middleware (e.g., ROS2, DDS) and distributed software architectures.

Trajectory Optimization: Hands-on experience with numerical trajectory optimization methods (e.g., MPC, QP/Nonlinear optimization, interior-point methods) and optimization solvers (e.g., OSQP, Ipopt, Ceres Solver).

The base salary range for the Software Engineer position is $141,463–$235,182 annually, and for the Senior Software Engineer position is $169,783–$282,264 annually, in addition to bonus, equity, and benefits.

The base salary range for the Software Engineer position is $141,463-$235,182 annually, and for the Senior Software Engineer position is $169,783-$282,264 annually, in addition to bonus, equity, and benefits.
Model Deployment Pipelines: Own the end-to-end deployment pipeline for deep learning mapping models-from Python-based training and ONNX optimization to highly efficient runtime execution in C++.
Within the applicable range, individual compensation is based on the work location as well as other factors, including job-related skills, experience, and relevant education and training.

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.

This listing is sourced directly from DiDi Labs's careers page and normalized into a canonical job model.