The Prediction and Behavior Modeling team is looking to add a Principal Research Scientist to help us build data-driven models for Perception, Prediction, and Planning. Your models will help us understand surrounding traffic, predict what other road users will do, and determine how to drive. Your machine learning, data analytics, and applied mathematics experience will inform your pragmatic approach to making a more intelligent autonomous vehicle. Does this sound like you?
What you'll be doing:
- Dive into data to understand behaviors of road users such as cars, bikes, and pedestrians
- Develop probabilistic models to predict how other road users may move and interact with our car, and evaluate their performance on real-world and simulated data sets
- Research data-driven driving policies for planning and decision-making
- Present results to colleagues and publish at conferences
- Influence our technical direction and research plans
- MS or PhD in computer science, robotics, or similar field, with 5+ years practical experience in robotics, machine learning, and analysis of large data sets
- In-depth understanding of common Machine Learning and Deep Learning algorithms, and their application to real-world systems
- Fluency in Python, including standard deep learning and scientific computing libraries
- Excellent skills developing software in a team setting
- Excellent skills for working with large data sets
- Strong applied math background
Bonus points (not required):
- Experience developing machine learning solutions for autonomous vehicles or robots
- Publications and patents encouraged. Team has one paper currently at CVPR (https://arxiv.org/abs/1911.10298).
- Joining a small team of 10, which offers the opportunity to contribute across multiple disciplines (perception, prediction, planning, infrastructure).
- Speaking opportunities are encouraged and supported
- Will closely collaborate with ML team for infrastructure and prototype