Senior or Staff Research Engineer, Motion & Behavioral Planning
Gatik is the leader in autonomous middle mile logistics. We deliver goods safely, quickly, and efficiently in our fleet of medium-duty trucks, connecting people and communities to the goods they really need. With every delivery, we're making the supply chain more reliable, keeping costs low, driving sustainability, and making the roads safer for all road users.
At Gatik, we believe in establishing new standards of success for the autonomous trucking industry every day. In 2021, we launched the world's first fully driverless commercial delivery service with Walmart, a historic milestone that's changing the way we view goods movement forever.
Gatik is a place to learn, lead and grow alongside industry veterans who are defining the future of logistics, and we want you to help us shape the next chapter in our journey.
We are seeking a tech lead for our planning team to build motion planning and decision-making systems and help mature new products all the way through to production. Our planning team calculates safe paths for the autonomous vehicle to follow using mapping data, localization data, waypoints, and predicted actors around the vehicle. Your contribution will improve the planning for emergency situations and planning for complicated maneuvers, such as loading dock access, variable lane changes, and lane closures.
Through effective collaboration with our engineering disciplines, you will guide our efforts to build improved planning from design all the way through to production. We are looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
- Build and improve algorithms throughout the motion planning stack, which could include things ranging from route planning, trajectory optimization, and decision making
- Develop policies and plans to manage multi-actor interactions and plans under uncertainty
- Integrate remote guidance requests and autonomy behaviors into the remote assist system
- Take algorithms from conception to implementation and deployment
- Test algorithms in simulation, in-vehicle in a controlled environment, and ultimately in-vehicle in the field
- Contribute to the behavior prediction of traffic participants perceived around the autonomous vehicle
- Develop efficient Deep Learning architectures that run in real-time or other resource-constrained settings
- Support all technical aspects of development
- Expertise in large-scale cloud infrastructure, e.g. G-Cloud or AWS
- Experience with ROS/ROS2 or other middleware systems
- Industry experience with software development for AVs
- Experience in code optimization or high-performance computing
- Experience writing numerical optimization algorithms
- Experience working with large data sets and HD map data
- Experience in applying machine learning and probabilistic behavioral models for planning problems (e.g. Imitation Learning, Behavior Prediction, Reinforcement Learning)
- Experience in state-of-the-art planning algorithms.
- Background in optimization, statistics, linear algebra
- Experience with C/C++
Working at Gatik
At Gatik, we connect people of extraordinary talent and experience to an opportunity to create a more resilient supply chain and contribute to our environment’s sustainability. We are diverse in our backgrounds and perspectives yet united by a bold vision and shared commitment to our values.
From our offices in the Bay Area, Toronto, and Texas, we pursue big goals with a relentless focus. We are builders who focus on delivering for our customers and each other. We recognize that the path toward excellence balances thoughtful debate with aligned action.
Individuals seeking employment at Gatik are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law.
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Autonomous Delivery Network for the Middle Mile