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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 /Sr. Software Engineer to join our team and develop the core decision-making and motion planning systems for our autonomous vehicles. In this role, you will be responsible for creating the algorithms that enable smooth, safe, and intelligent navigation in complex environments. You will tackle challenges across the full motion planning stack, from high-level behavioral reasoning to low-level trajectory optimization. Responsibilities Design and implement the core motion planning logic that determines the vehicle's high-level actions (e.g., lane changes, merges, yields, and interactions with other agents). Develop and optimize the motion planning algorithms that execute behavioral decisions, integrating Geometry Reasoning (path) and Speed Reasoning (velocity) into a cohesive trajectory. Architect and enhance the geometry system for generating geometrically feasible and compliant paths. Architect and refine the velocity system for generating context-aware, comfortable, and safe velocity profiles. Model complex driving scenarios and agent interactions to create a robust world model for the behavioral planner. Design different costs for trajectory ranking to trade off ETAs, comfort and safety of the vehicle behaviors. Conduct in-depth analysis, testing, and debugging of the system's performance in various scenarios, leading root cause investigations. Collaborate with Prediction, Perception, and Control teams to ensure a seamless flow from environmental understanding to physical vehicle motion. Qualifications B.S./M.S. in Computer Science, Robotics, or a related field. Experience in autonomous systems, robotics, or automotive software development. Strong proficiency in C++ for implementing complex, real-time algorithms. Solid understanding of robotics fundamentals, including decision-making, motion planning, control theory, trajectory ranking, search and optimization algorithms etc. Related experience in one or more of the following: motion planning, trajectory optimization and world environment reasoning, trajectory ranking and cost design. Preferred Qualifications PhD or internship experience related to robotics planning system designs. Knowledge of vehicle dynamics and longitudinal/lateral control systems. Solid understanding of machine learning principles, reinforcement learning and related algorithms. 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. Our salary ranges are determined by the role, level, and location. 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. I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa

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 deep learning mapping models—from Python-based training and ONNX optimization to highly efficient runtime execution in C++. 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. Qualifications Education: B.S./M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field. Experience: 3+ years (Software Engineer) / 5+ years (Senior Software Engineer) of experience in autonomous driving, robotics architecture, or spatial computing. Software Mastery: Expert proficiency in production-grade C++ (Modern C++14/17/20, multi-threading, memory management) and strong prototyping proficiency in Python. 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. Preferred Qualifications 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). Advanced Mapping Experience: Hands-on experience working with HD map formats (Lanelet2, OpenDRIVE) and modern end-to-end learning frameworks (e.g., MapTR, VectorNet) that leverage query-based BEV perception. Deep Learning Runtime & Deployment: Proven track record of exporting complex deep learning architectures via ONNX and deploying them into real-time C++ production environments using TensorRT. Anomaly Detection: Proven track record of developing algorithms for map anomaly detection, sensor-to-map misalignments, or online scene-change identification. Safety-Critical Systems: Knowledge of real-time operating systems (RTOS), deterministic software execution, and safety-critical software design principles. 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. Our salary ranges are determined by the role, level, and location. 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. I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa

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 motivated PhD graduate with a strong research background in motion planning, robotics, or autonomous systems. In this role, you will apply your expertise in algorithm design and system integration to help develop next-generation planning capabilities for autonomous vehicles. Responsibilities Implement novel solutions for Behavioral Planning, enabling high-level decision-making for lane changes, merges, yields, and multi-agent interactions. Design and optimize motion planning algorithms that integrate geometry-based path reasoning and context-aware speed reasoning into smooth, safe trajectories. Develop and improve core geometry and velocity planning systems to ensure feasibility, compliance, and comfort across diverse driving scenarios. Model complex driving environments and agent behaviors to create a robust world representation for planning under uncertainty. Formulate cost functions and optimization frameworks that balance safety, comfort, and efficiency in trajectory selection. Analyze, test, and debug system performance through simulation and real-world data, conducting root-cause investigations and proposing enhancements. Collaborate with researchers and engineers across Perception, Prediction, and Control to ensure an integrated, reliable autonomy stack. Qualifications Recently completed or soon-to-complete PhD in Robotics, Computer Science, Electrical Engineering, or a related field. Research or Internship experience in one or more of the following: Motion planning algorithms (optimization, sampling, graph/search-based methods) Behavioral planning and decision-making under uncertainty Trajectory optimization and control Multi-agent interaction modeling Proven research ability demonstrated by publications in top-tier conferences (e.g., RSS, ICRA, IROS, CVPR, NeurIPS, CoRL). Hands-on experience in C++ for implementing complex, real-time algorithms. Excellent analytical and communication skills, with a collaborative mindset. For Internship Applicants: This role offers a clear pathway, with top-performing interns receiving the opportunity to convert to a full-time engineer upon successful completion of the program. The hourly rate for the Intern position in the selected city is $46. Interns will also be eligible for Intern benefits. Applications are accepted on an ongoing basis. This posting is for an existing vacancy. I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa

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 At DiDi Autonomous Driving, we firmly believe that the future of mobility goes beyond simply "utilizing AI"—it will be fundamentally reimagined and entirely driven by an AI-Native architecture . We are seeking a visionary, highly technical, and mission-driven Staff / Principal Forward Deployed Engineer (FDE) to act as the ultimate catalyst for our company-wide AI transformation. In this strategic, high-impact leadership role, you will combine cutting-edge Large Language Model (LLM) expertise, robust systems architecture design, and a proven track record of enterprise-level AI scaling. You will embed deeply with our core engineering teams to evolve our traditional R&D organization into a truly AI-Native powerhouse. Key Responsibilities AI Infrastructure & Platform Architecture: Spearhead the evaluation, selection, and deep integration of frontier LLM ecosystems (e.g., Llama, Hugging Face) and commercial AI platforms. Own the architectural design of our unified, distributed AI platform spanning complex data processing, model training, inference pipelines, and evaluation frameworks. Forward Deployed Execution: Embed directly with core autonomous driving teams (Perception, Prediction, Planning & Control, and Simulation) via the FDE model. Pinpoint engineering bottlenecks, eliminate friction, and translate complex AI capabilities into production-ready internal ecosystems (e.g., AI DevOps, AI Copilots). LLMOps / MLOps Orchestration & Optimization: Design and implement highly resilient, scalable automation pipelines for LLM deployment, monitoring, and continuous feedback loops. Optimize GPU cluster utilization, minimize inference latency, and maximize throughput across large-scale production environments. Technical Roadmap & Vision: Keep a strong pulse on breakthrough trends in AGI and systems engineering. Act as a "super-connector" between external technological innovations and internal systems, ensuring our AI infrastructure maintains a 1-3 year competitive edge. Qualifications & Experience Architectural Vision + Hands-on Execution: A proven technical leader who can design complex, system-level architectures while maintaining a fierce passion for writing core code, debugging deep system issues, and optimizing low-level execution paths. Proficiency in core languages such as C++, Python, Java, JavaScript, etc. Cross-Functional Influence: Demonstrated ability to build technical authority, align priorities, and drive diverse engineering teams (Algorithms, Infrastructure, Hardware) toward adopting an AI-first engineering paradigm without relying on formal administrative authority. Enterprise AI Transformation: Proven experience leading or heavily contributing to a large-scale corporate "AI-native transformation," or a track record of building enterprise-grade AI/ML platforms from 0 to 1. Deep AI Tech Stack Expertise: Thorough hands-on deployment, tuning, and optimization experience with mainstream AI infrastructure tools and frameworks, including but not limited to PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, and Megatron-LM. Hardcore AI Infra Experience: Years of deep, practical experience in distributed LLM training/inference optimization and large-scale compute cluster infrastructure & operations (I&O). Preferred Qualifications Domain Expertise: Familiarity with autonomous driving algorithms (Perception, Planning, Control, Simulation), robotics, physics-based simulation engines, or ultra-large-scale ML training/serving clusters is highly preferred. Senior Industry Track Record: 8-10+ years of professional engineering depth in systems software, core cloud infrastructure, or production-grade machine learning platforms. Agentic Frameworks & Developer Productivity: Hands-on experience building custom AI Copilot applications, autonomous Multi-Agent Frameworks, or high-tier developer productivity platforms. Thriving in Complexity: Proven success steering core project delivery amidst complex business logic, fast-paced/high-pressure environments, or mission-critical systems. Technical Influence: An active contributor to the broader tech community (e.g., open-source maintainer/owner, author of high-quality technical blogs/papers, or speaker at premier industry AI/ML conferences). The base salary range for this full-time position is $255,000 -$351,000 annually in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa