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.

• Perform optimization on simulation software under the guidance of profiler.
• Identify and resolve algorithm deficiencies that affects simulation determinism.
• Implement new simulation capabilities that fits new hardware.

• PhD, Master’s students or senior undergraduate students majoring in Computer Science or a related field.
• Strong C++ development skills with experience in performance-critical applications.
• Deep understanding of computer architecture.
• Great communication skills that fosters cross-team collaboration.
• Familiarity with robotics (perception, motion planning) is a plus.
• Experience with GPU/CUDA programming is a bonus.
  

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 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 an experienced and mission-driven Staff System Safety Engineer, Autonomy to lead the safety strategy and deployment readiness of our fully autonomous driving systems. In this role, you will define and implement the safety frameworks, release policies, and system-level engineering processes that enable safe and scalable unmanned operations. You will act as a technical leader in system safety, ensuring that our vehicles meet rigorous safety standards while advancing toward large-scale commercial deployment.

Responsibilities

• Own the safety evaluation and release strategy for unmanned autonomous driving operations, defining clear criteria for system release, degradation, and fallback under varying operating conditions.
• Design, implement, and champion the safety-related systems engineering framework, including safety requirements, system architecture, and Verification & Validation (V&V) plans.
• Conduct systematic assessments of unmanned operational workflows, emergency protocols, and supporting tools/platforms to ensure safety and operational completeness.
• Develop and institutionalize safety evaluation methodologies and metrics frameworks, translating safety goals into quantifiable, verifiable, and continuously tracked indicators.
• Serve as the technical lead for safety-related incident review and analysis during unmanned operations, driving continuous improvements in system design, test coverage, and operational procedures.
• Collaborate cross-functionally with Software, Product, Operations, and Safety teams to support leadership decisions regarding unmanned deployment, city expansion, and operational scaling.

Qualifications

• Bachelor’s or higher degree in Computer Science, Software Engineering, Systems Engineering, or a closely related technical field.
• 5+ years of industry experience in systems engineering, safety engineering, autonomous systems, or a directly related field.
• Strong systems thinking with the ability to decompose complex safety challenges and drive practical, scalable solutions.
• Demonstrated ability to collaborate across teams, influence stakeholders, and take ownership of safety outcomes.
• Experience working in a fast-paced environment with multiple parallel projects and ambiguous requirements.

Preferred Qualifications

• Professional experience in safety-critical autonomous vehicle deployment or large-scale robotic systems operations.
• Background in functional safety (ISO 26262, SOTIF) or safety assurance of unmanned systems.
• Hands-on experience with safety validation tools, simulation-based V&V, or operational safety monitoring platforms.
• Proven track record of defining release policies or safety readiness criteria for real-world autonomous systems.

The base salary range for this full-time position is $178,286-296,400 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

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 Behavioral 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: behavioral planning, motion planning, behavior 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 this position is $129,189-$214,776 for Software Engineer and $148,594-247,038 for Sr. Software Engineer, 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

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

The Foundation Model Team focuses on building large-scale foundation models for multi-agent behavior prediction and autonomous vehicle planning. By leveraging DiDi Voyager’s unparalleled driving data, we train highly robust and generalizable deep learning systems that enable safe and intelligent autonomous driving at scale.

Our models serve as the core intelligence of the autonomous driving stack, enabling vehicles to understand complex traffic scenarios, anticipate agent behavior, and make safe and efficient driving decisions.

We operate at the intersection of large-scale machine learning, autonomous driving, and foundation model research, pushing the frontier of multi-agent prediction and planning.

Responsibilities

As a member of the Foundation Model Team, you will:

• Design and train large-scale deep learning models for:

• Multi-agent trajectory prediction

• Behavior and intent prediction

• Planning and decision-making

• Build foundation model architectures (Transformers, Diffusion, Flow-based models, Decision models, VLM/VLA)

• Develop scalable training pipelines across hundreds to thousands of GPUs

• Work with massive real-world datasets and build high-quality data pipelines

• Optimize models for latency, reliability, and on-vehicle deployment

• Collaborate closely with perception, mapping, simulation, and systems teams

• Drive research ideas into production systems used by real autonomous vehicles

Qualifications

• Strong background in machine learning, deep learning, or robotics

• Experience with PyTorch / JAX / TensorFlow

• Solid understanding of modern neural architectures (transformers, diffusion, auto-regressive)

• Strong coding skills in Python and C++

• Passion for building real-world, safety-critical AI systems

Preferred Qualifications 

• BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related field

• Experience in autonomous driving, robotics, or embodied AI

• Experience training large models on distributed GPU clusters

• Experience with trajectory prediction, planning, or decision-making systems

• Publications in top ML / robotics conferences (NeurIPS, ICML, ICLR, CVPR, RSS, CoRL, etc.)

The base salary range for this position is $129,189-$247,038 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