The Mission Planner team at Zoox is responsible for creating high-level routes for our autonomous vehicles to transport passengers to their destinations. You will work closely with our Cloud Services team to facilitate pick-up and drop-off requests, along with live traffic data among other inputs. You will also integrate closely with the decision-making and trajectory planning and controls teams to allow dynamic planning. This team will enable the core ability for our vehicles to choose the best routes through cities and adapt in real-time.
We are seeking an engineer who is passionate about tackling the complexities of mission planning in dynamic cities. You should be driven to contribute innovative solutions to architecture and design and take responsibility for significant software components. If you like to work close to the robot platform and enjoy experiencing your developed software in the robot, we would like to hear from you.
In this role, you will:
Develop mission planner algorithms, including graph search and integration with behavioral planning
Integrate and test your developed applications in the robot, learn and make improvements.
Work collaboratively with passionate team members to support the integration of software components from all teams throughout Zoox.
Set the short and long term technical direction for the team and collaborate on the broader company-wide directions
Coordinate cross-functional initiatives with other teams across Mission Planning, Behavioral Planning and Cloud Services.
Qualifications
BS/MS in Computer Science, Robotics, or a related field and 2+ years of industry experience
Programming skills in C++
Understanding and experience with a variety of graph search techniques (A*, D*, Dijkstra …)
Model real-world problems using Markov Decision Processes (MDPs) or related frameworks
Develop scalable solutions for sequential decision-making under uncertainty and constraints
Demonstrated ability to write code for a shipped product (commercial robotics, drones, consumer devices, automotive)
Bonus Qualifications
PhD in computer science or related field
Experience with autonomous robots
