Pony.ai is looking to solve complex real-world problems in autonomous mobility by developing and deploying advanced machine learning models, including foundation models, VLMs, and LLMs, to ensure the safest autonomous driving capabilities on a global scale.
Requirements
- Solid understanding of data structures, algorithms, parallel computing, code optimization and large scale data processing.
- Experience in applied machine learning including data collection and analysis, evaluation and feature engineering.
- Expertise in C++/Python.
- Experience in deploying deep learning algorithms for real time applications, with limited computing resources.
- Experience in convex optimization, computational geometry or linear algebra.
- Experience in GPU/CUDA/TensorRT
Responsibilities
- Work with experts in the field of self-driving vehicles on software architecture and design, system and module design, evaluation metrics, specification and implementation of test and regression frameworks.
- Design and develop large-scale foundation models trained on vast of real world data
- Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems; scale them to data pipelines; and streamline them to run in real-time on the cars.
- Develop and deploy deep learning models, including vision language models (VLMs) and Large Language Models (LLMs)
- Optimize deep learning models to run robustly under tight run-time constraints.
Other
- Master in Computer Science, or at least 2 years of equivalent industry experience in similar technical fields.
- Strong communication skills and team spirit.
- PhD in Deep Learning, Machine Learning, Robotics, Natural Language Processing, or similar technical field of study.
- Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/ICLR/AAAI/IJCV/PAMI
- Experience in applying ML/DL for behavior prediction, imitation learning, motion planning.
