Chief Scientist - Autonomous Vehicle

OUR CLIENT, established in 2017, is a national high-tech enterprise and a Chinese unicorn company. It focuses on the large-scale deployment and commercial operation of L4 autonomous buses. The company possesses over 1000 invention patents and copyrights.

Its core shareholders include Tencent, JD.com, CITIC Capital, and several local investment platforms. Currently in the pre-IPO stage, OUR CLIENT aims to be a leading global provider of autonomous buses. OUR CLIENT has already established operations in 10 cities including Beijing, Shanghai, and Tianjin. With regular operation in multiple cities and scenarios, forming the world's largest autonomous bus fleet, MOGOX exclusively launched its first L4-level RoboBus official website in Singapore in October 2025. Regular operation will commence on core bus routes, marking its official entry into the overseas public transportation system. Simultaneously, OUR CLIENT exclusively obtained the patent for Zhongtong Bus's autonomous bus kit solution, promoting large-scale deployment and batch delivery.

Leading Autonomous Driving Solution

OUR CLIENT, powered by data and AI, is committed to building a leading autonomous driving brand, RoboBus.

Recruiting Chief Scientist

Role Located in Beijing

1. Job Title

Overall Direction and Architecture Design of Autonomous Driving Algorithms

Leading the development of public autonomous driving technology direction and roadmap, covering multiple vehicle types/multi-scenarios, supporting L4 capability in urban environments

Enhancing the capability of classic algorithms and ensuring system stability Guide and improve key algorithm modules in classic technologies, such as perception, prediction, and policy planning, and collaboratively design key algorithm performance optimization strategies to ensure that the algorithms can meet the requirements for L4 deployment.

Prioritize AI capability guidance and deployment, leading the team to promote one-stage/two-stage end-to-end algorithm deployment, as well as multi-sensor BEV fusion and 1VLA (Vision-Language-Action). Apply reinforcement learning. Guide the optimization of data closed systems, including data mining, high-quality sample selection, automatic monitoring, and model comparison evaluation.

Develop and cultivate a technical talent pool.

Recruit and cultivate core algorithm engineers with algorithmic foundation and practical skills.

Establish a research mechanism, a technology sharing and cultural and innovation incubation mechanism to enhance the overall influence and innovation capabilities of the algorithm team.

II. Job Requirements

1. Education and Experience Background: Master's degree or above, PhD preferred.

Specializations include: Human Intelligence, Automation, Robotics, Computer Vision,

Machine Learning, Motor Engineering, etc. 8+ years of experience in autonomous driving or intelligent driving technology, 5+ years of experience leading a core algorithm team.

Previous experience as a lead algorithm engineer/core leader in a top domestic/international autonomous driving company.

Possesses the drive and passion to lead large-scale L4 deployments, with ample production/real-world implementation case studies to prove it.

Technical Vision and Cutting-Edge Exploration Capability:

Has multi- domain technical vision and production experience, such as perception, prediction, planning, two-stage/one-stage, VLA/world modeling, etc. Able to integrate practical engineering capabilities and lead teams to translate cutting-edge research into practical applications. Management and Collaboration Capability: Capable of leading algorithm teams or cross-departmental matrix projects. Familiar with collaborative models for algorithms and systems, simulation, testing, product development, vehicle modification, etc. Has a clear ability to balance delivery goals and research innovation.

Priority given to candidates with experience in deploying autonomous driving production vehicles or large- scale road testing systems. Has published papers at top conferences such as CVPR, ICRA, NeurIPS, and CoRL. Familiarity with China's road environment and policies, and preference will be given to vehicles with L4 city operational experience.