--- title: 'Research Intern, Scene Understanding and Planning at DiDi Labs' canonical: 'https://feeny.ai/job/research-intern-scene-understanding-and-planning-didi-labs-san-jose-re06bc12hdvy' type: 'job' last_seen: '2026-11-04' --- # Research Intern, Scene Understanding and Planning at DiDi Labs - **Company:** DiDi Labs - **Location:** San Jose, CA - **Posted:** 2026-10-18 - **Last confirmed live:** 2026-11-04 - **Apply:** https://job-boards.greenhouse.io/didi/jobs/8299748 ## Job description ## About Didi Autonomous Driving Founded in 2016, DiDi's autonomous driving unit is dedicated to developing Level 4 autonomous driving technology to make transportation safer, more efficient, and accessible. In 2019, the unit became an independent company, Voyager, to accelerate technology development, commercialization, and large-scale deployment. By combining DiDi's unique data advantage, operational expertise, and mobility ecosystem, we aim to build a reliable, scalable autonomous fleet that integrates seamlessly with human-driven services. Driven by real-world customer needs and a strong commitment to safety and user experience, our mission is to deliver autonomous mobility solutions that create meaningful value for riders and communities. ## About the Role We want our vehicles to understand the physical world as it is right now, instead of relying on a map drawn long ago. Roads change, and the world a car actually drives in is always more complex than any static record of it. We are seeking a Research Intern to help give our planner a more accurate and up-to-date picture of the world, so the vehicle handles complex real-world scenes more robustly. In this role, you will take on hard, open problems from real-world driving and solve them with frontier research methods. You will report directly to the team lead and work on the problem from definition to validated solution. Strong results will often be worth publishing, and we will support you in writing them up, but the goal is to solve problems that matter to the product. ## Responsibilities - Survey the latest research in scene understanding, prediction, and planning, and turn it into practical approaches that fit our system and constraints. - Design and implement deep learning models that build a richer, real-time understanding of the driving environment from onboard sensors and other available sources. - Train and evaluate models on large-scale data from our driving logs and on public benchmarks, and lead failure analysis to find out where and why models fall short. - Define metrics and evaluation methods that connect perception quality to how the vehicle actually drives. - Turn successful prototypes into solutions that work with our planning stack, with help from production engineers. - Collaborate with Perception, Prediction, Planning, and Mapping teams so results move from experiment to product. ## Qualifications - Currently enrolled in an M.S. or Ph.D. program in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related field, for the full duration of the internship. - Available for a full-time onsite internship of 3–6 months; start dates are flexible. - Strong programming skills in Python, and experience with modern deep learning frameworks such as PyTorch or JAX. - Hands-on experience designing, training, and debugging deep learning models for computer vision, 3D perception, or sequential decision-making. - Solid understanding of autonomous driving fundamentals, including perception, prediction, and motion planning. - Ability to read research critically, form hypotheses, and turn them into well-controlled experiments. - Excellent communication and collaboration skills. ## Preferred Qualifications - Publications at top venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, ICRA, IROS, CoRL or IV. - Experience with multi-modal sensor fusion (camera, lidar, radar) or BEV representations. - Experience with transformers, graph neural networks, or other structured scene representations. - Experience with uncertainty estimation, or with learning-based prediction or planning. - Experience with large-scale model training and data pipelines. - Experience with public autonomous driving datasets such as nuScenes, Argoverse 2, or the Waymo Open Dataset. - Proficiency in C++ (CUDA is a plus) and experience with robotics systems. The hourly rate for the Intern position in the selected city is $46. 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 DiDi Labs ## Company Overview - **One-liner**: DiDi Labs is the U.S. research and development arm of DiDi, focused on advancing Level 4 autonomous driving technology through large-scale AI models and real-world ride-hailing data. - **Entity Type**: Private (subsidiary of DiDi Global Inc., which is not publicly traded) - **Headquarters**: Mountain View, California, United States - **Founded**: 2017 (DiDi Labs); parent company Didi Chuxing founded in 2012 - **Founders**: DiDi Labs was launched under the leadership of Cheng Wei (DiDi founder and CEO) and initially led by Dr. Fengmin Gong, Vice President of DiDi Research Institute. ## Core Business - **Primary Industry**: Autonomous driving (Level 4), artificial intelligence, mobility technology - **Target Customers**: B2B (integrated into DiDi’s shared-mobility fleet), enterprise partnerships (e.g., automotive OEMs, cities for smart transportation) - **Mission**: Develop Level 4 autonomous driving technology to make transportation safer and more efficient, and integrate it into a shared-mobility fleet to generate broad social value. ## Products & Services - **VLA (Vision-Language-Action) Foundation Models**: Large-scale deep learning systems for multi-agent behavior prediction and autonomous vehicle planning, built on DiDi’s massive real-world driving dataset. - **Behavioral & Motion Planning Systems**: Core decision-making and trajectory optimization algorithms that enable safe, smooth navigation in complex urban environments. - **AI Research (Computer Vision, NLP, Speech, Mapping)**: Through DiDi AI Labs (China-based but collaborative), the company develops speech interaction, smart mapping, and perception solutions. - **Autonomous Vehicle Testing & Fleet Operations**: DiDi Autonomous Driving operates test fleets in the United States and China, and runs open-source challenges (e.g., Udacity Self-Driving Car Challenge). ## Market Standing - **Valuation**: Not publicly disclosed for DiDi Labs; parent DiDi Global was valued at over $60 billion during its 2021 IPO (now delisted and private). - **Key Metric**: Total funding for DiDi exceeds $20 billion across multiple rounds (SoftBank, Tencent, etc.). DiDi Labs benefits from parent’s resources. - **Notable Investors/Partners**: DiDi’s investors include SoftBank Vision Fund, Tencent, Uber, Apple, and others. DiDi Labs partners with Udacity, and its team includes security expert Charlie Miller. - **Growth Signals**: Independent autonomous driving unit established in 2019; active hiring in 2025 for VLA and motion planning roles; integration with DiDi’s massive ride-hailing network (over 500 million users) provides unmatched real-world data. ## Competitive Advantages - **Massive Real-World Data**: Access to DiDi’s billions of trips across Asia, Latin America, and Australia gives the team proprietary training data for behavior prediction and planning. - **Integration with Shared Mobility**: Autonomous fleet can be deployed directly into an existing ride-hailing platform, offering a clear go-to-market path. - **Top Talent & Research**: Deep roster of AI researchers, published in top conferences (NeurIPS, CVPR, ICLR, etc.), and strong collaboration with global research network. - **Open Innovation**: Hosts open-source challenges and engages with the broader self-driving community. ## Strategic Focus - **Current Priorities**: Scaling VLA foundation models for multi-agent prediction and planning; deploying Level 4 autonomous vehicles in operational domains; optimizing latency and safety for production deployment. - **Direction for Growth**: Expanding the autonomous fleet, deepening partnerships with cities, and building the “smart transportation ecosystem” through AI-driven infrastructure. ## Why Work Here - **Cutting-Edge AI at Scale**: Work on large-scale distributed training (hundreds to thousands of GPUs), transformers, diffusion models, and real-time planning for safety-critical systems. - **Impact**: Directly contribute to autonomous driving technology that could transform urban mobility and reduce traffic accidents. - **Compensation & Benefits**: Competitive base salary (e.g., $129k–$247k for ML Engineer, plus bonus, equity, and benefits). Roles in Mountain View with hybrid/office expectations. - **Culture & Perks**: Collaboration with world-class researchers, access to massive datasets, and a mission-driven environment focused on safety and innovation. - **Work Model**: Based in Mountain View, CA; roles are likely on-site or hybrid given the hands-on nature of autonomous vehicle development. ## Sources 1. [Job Board - Machine Learning Engineer, VLA](https://job-boards.greenhouse.io/didi/jobs/7975368) 2. [Job Board - Software Engineer, Motion & Behavioral Planning](https://job-boards.greenhouse.io/didi/jobs/7975371) 3. [PRNewswire - DiDi Launches U.S. Labs in Silicon Valley](https://www.prnewswire.com/news-releases/didi-launches-us-labs-in-silicon-valley-to-build-global-nexus-of-innovation-300420435.html) 4. [Golden - DiDi Labs Company Profile](https://golden.com/wiki/DiDi_Labs-GE84KD8) 5. [DiDi Official - AI Labs Page](https://www.didiglobal.com/science/ailabs) ## Other roles at DiDi Labs - [Sr. / Staff Software Engineer, Infrastructure (Autonomy)](https://feeny.ai/job/sr-staff-software-engineer-infrastructure-autonomy-didi-labs-san-jose-46z14fjyjr4e) — San Jose, CA - [Staff/Principal AI Transformation Engineer](https://feeny.ai/job/staff-principal-ai-transformation-engineer-didi-labs-san-jose-0q3b0yenvgj4) — San Jose, CA - [ML Engineer, Motion Planning](https://feeny.ai/job/ml-engineer-motion-planning-didi-labs-san-jose-03dysefnhh2g) — San Jose, CA - [Sr. /Staff System Safety Engineer, Autonomy](https://feeny.ai/job/sr-staff-system-safety-engineer-autonomy-didi-labs-san-jose-4n27gkmr8zry) — San Jose, CA - [Software Engineer, Motion Planning](https://feeny.ai/job/software-engineer-motion-planning-didi-labs-san-jose-9p04hs5ps8a0) — San Jose, CA - [Motion Planning Engineer (PhD, Intern)](https://feeny.ai/job/motion-planning-engineer-phd-intern-didi-labs-san-jose-ggrryq4gd28h) — San Jose, CA - [Senior/Sr. Staff AI Infrastructure Engineer, Inference & Optimization](https://feeny.ai/job/senior-sr-staff-ai-infrastructure-engineer-inference-optimization-didi-labs-san-zg861r8xhm7c) — San Jose, CA - [Software Engineer / Sr. Software Engineer, Planning Selection Autonomy](https://feeny.ai/job/software-engineer-sr-software-engineer-planning-selection-autonomy-didi-labs-qp2kzcd84107) — San Jose, CA