didi · San Jose, CA
Skills: Python
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 Autonomous driving software today improves mostly by hand: engineers collect data, train models, and tune modules. This role explores a different approach, in which AI agents take part in that work. Agents propose changes to policy code, data, training recipes, or model code. They then evaluate the results, diagnose failures, and turn verified fixes into reusable skills and data for the next round. With DiDi Voyager's real-world driving data and large-scale evaluation infrastructure, the goal is a loop that produces improvements that generalize across scenarios, pass safety gates, and reach the vehicle. The role combines machine learning, agentic systems, and autonomous driving, and will help shape both the onboard architecture and how driving software is developed. Responsibilities Build agentic harnesses for autonomous driving. Agents get permissioned access to the driving stack, data, training infrastructure, and evaluation environments, along with automatic scenario setup and pass/fail checks, so they can run experiments without a person in every step. Develop recursive self-improvement (RSI) loops. These include failure mining, candidate generation, evolutionary search, and targeted data generation aimed at the policy's current weaknesses. Each round should also improve the process that produces the next one. Curate a r…
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