What you will be doing:
Maturing and productizing autonomous vehicle features entails a diversity of activities.
Defining and developing of algorithms to solve planning and decision making problems, integrate them into our software stack and mature them to production quality.
Solving problems of how to combine data driven (machine learning) and classical solutions to create a robust pipeline that covers as many of the real world situations as possible.
Defining and verifying product requirements through building and enhancing existing tools and methodologies, detailed analyses, testing in simulation and on the road.
Collaborate with a diverse group of engineers and researchers of other domains including perception, mapping and vehicle control, as well as our internal safety teams to perform safety analysis.
What we need to see:
Advanced degree student pursuing MSc or Phd in Computer Science or Engineering a must!
Strong software engineering skills, knowledge of both C/C++ and Python, along with a familiarity programming with GIT in Linux (Ubuntu) or another Unix based system a must!
Background in robotics, including a good understanding of kinematics of rigid bodies. Hands-on experience working on machine learning solutions.
Ability to think analytically and solve technical problems in a compute constrained system, ability to multitask and prioritize in a fast paced environment and excellent communication skills
Ways to stand out from the crowd:
Experience working on Imitation Learning, Reinforcement Learning, Inverse Reinforcement Learning, Optimal Control, Search algorithms (A*, D*, RRT, Reinforcement Learning, MCTS, etc.) in the industry or academia.
Prior experience in delivering a product-level planner for active safety or autonomous driving functions.
