Job Description
The role involves developing machine learning models for predicting the behavior of surrounding agents and planning optimal trajectories for autonomous vehicles, focusing on autonomous driving behavior and generative modeling techniques.
Key Responsibilities
- Develop novel algorithms in agent behavior prediction and AV planning in interactive scenes
- Conduct research on combined prediction and planning models
- Work on marginal, conditional, and joint prediction
- Develop robust prediction and planning metrics for assessing behavior systems
- Push forward generative AI methods for use in the Autonomy Stack
- Test ML models in simulation to ensure robust performance and generalization
- Analyze model performance and identify areas for improvement
- Participate in AI Research team activities targeting internal education and external scientific image
- Collaborate with Production teams to deploy ideas
- Propose new ideas and build on state-of-the-art knowledge
Requirements
- You have a Ph.D. in one or more of the following areas: Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related field.
- You have at least 1-3 years of hands-on experience in one or more of the following areas: Autonomous Driving, Robotics, or Deep Learning.
- You have at least 1-3 years of research experience in one or more of the following areas: Generative Modeling, Behavior Prediction and/or Planning, Statistics, Probability theory.
- Deep knowledge of Autonomous Driving Behavior including various formats of maps (rasterized, vectorized), Diffusion modeling (different forms of guidance, sampling optimization, probability estimation), Transformer Decoding, Flow-based, VAE, and RNN-based generative approaches, Prediction vs Planning, Marginal vs Conditional vs Joint, Open vs Closed loop, and Imitation Learning approaches.
- Experience with simulation environments for autonomous vehicles, such as CARLA, Waymax, or similar platforms.
- Strong foundation in data structures, algorithm design, and complexity analysis.
- Expertise in programming languages and tools critical for high-performance computing in Python, C, and machine learning including Deep Learning frameworks like TensorFlow and PyTorch.
- Demonstrated ability to publish research findings in any of the top-tier technical journals and conferences such as ICRA, CoRL, IROS, ICLR, ICML, NeurIPS, AAAI, IJCAI, CVPR, ICCV, ECCV.
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