- Strong engineering experience applying ML-driven approaches to solve complex real-world problems, with a proven track record of translating research ideas into robust, production-quality systems and successfully deploying them.
- Experience integrating learning-based approaches with traditional rule-based or optimization-based planning systems to improve safety, efficiency, and robustness.
- Experience with closed-loop simulation, large-scale evaluation, and data-driven model iteration for autonomous driving.
- Experience mentoring junior engineers, supervising research interns, or leading small technical teams.
- Experience with road-structure representations, including lane graphs, topology reasoning, scene understanding, or uncertainty estimation in complex driving environments.
- Experience with end-to-end autonomous driving models, learned planners, vision-language models, or foundation models applied to driving and robotics.
- Experience deploying and optimizing ML models for real-time onboard inference, including TensorRT, CUDA, quantization, and compute or latency optimization.
- Publications at leading conferences such as CVPR, ICCV, ECCV, NeurIPS, CoRL, ICRA, IROS, or IV, or equivalent demonstrated technical impact in industry.
The annual base salary range for the Senior ML Engineer position is $169,783–$282,264, and for the Staff ML Engineer position is $203,726–$338,694. In addition to base salary, compensation includes bonus, equity, and benefits. The salary ranges are determined by role, level, and location. Individual compensation within the range depends on several factors, including work location, job-related skills, relevant experience, and 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