---
title: 'Motion Planning Engineer (PhD, Intern) at DiDi Labs'
canonical: 'https://feeny.ai/job/motion-planning-engineer-phd-intern-didi-labs-san-jose-md1kry2qmm4c'
type: 'job'
last_seen: '2026-09-09'
---

# Motion Planning Engineer (PhD, Intern) at DiDi Labs

- **Company:** DiDi Labs
- **Location:** San Jose, CA
- **Posted:** 2026-08-17
- **Last confirmed live:** 2026-09-09
- **Apply:** https://job-boards.greenhouse.io/didi/jobs/8131863

## 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 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 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

- [Software Engineer / Sr. Software Engineer, Planning Selection Autonomy](https://feeny.ai/job/software-engineer-sr-software-engineer-planning-selection-autonomy-didi-labs-znt50prkgrw8) — San Jose, CA
- [Software Engineer, Motion Planning](https://feeny.ai/job/software-engineer-motion-planning-didi-labs-san-jose-gj5n60m2bt8x) — San Jose, CA
- [Sr. /Staff System Safety Engineer, Autonomy](https://feeny.ai/job/sr-staff-system-safety-engineer-autonomy-didi-labs-san-jose-hr27mnazva4n) — San Jose, CA
- [Staff/Principal AI Transformation Engineer](https://feeny.ai/job/staff-principal-ai-transformation-engineer-didi-labs-san-jose-0kt7qqpjbfaz) — San Jose, CA
- [Technical Program Manager, Autonomy](https://feeny.ai/job/technical-program-manager-autonomy-didi-labs-san-jose-qqr86j3cpk46) — San Jose, CA
- [Sr. / Staff Software Engineer, Infrastructure (Autonomy)](https://feeny.ai/job/sr-staff-software-engineer-infrastructure-autonomy-didi-labs-san-jose-fgb84pk2gbty) — San Jose, CA
- [Software Engineer, Map Fusion & Planning](https://feeny.ai/job/software-engineer-map-fusion-planning-didi-labs-san-jose-g8fe119htkz6) — 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-09dry78v6mty) — San Jose, CA