At Gatik we're developing Level 4 automated light trucks and vans for business to business (B2B) short-haul logistics. Our autonomous vehicles reduce the high cost of urban logistics, while improving safety, increasing efficiency, reducing congestion and emissions, and allowing businesses to best serve the community.
Led by a team of AV researchers and engineers from Carnegie Mellon University, we are building new concepts and groundbreaking solutions for autonomous vehicles to ensure goods are transported between business locations both efficiently and affordably in city environments. With offices in Palo Alto and Toronto, we are dedicated to building commercial applications of AVs and aim to power the next generation of self-driving commercial fleets for urban logistics.
We're looking for high-energy, creative and collaborative candidates who would like to work in a fast-paced, execution-oriented team. If you are a software engineer who is curious and passionate about Level 4 autonomous driving, we'd like to meet you!
Develop machine learning models to predict agents' future trajectories, and classify agents' intents
Design and implement key components of planning stack responsible for defining the vehicle driving behavior
Develop sequential decision making models for safe and acceptable planning for self-driving vehicles
Develop efficient Deep Learning architectures that run in real-time or other resource constrained setting
Master's or Ph.D. degree in CS, Robotics or related field
3+ years of professional experience with software development for robotic systems
Experience with emerging deep learning based motion planning approaches (LSTMs, Deep Reinforcement Learning, Deep Q-learning, etc)
Solid technical foundation in CPU and GPU architectures, containers and numeric libraries
Extensive experience designing and building planners for AVs
Strong problem-solving skills - ability to troubleshoot complex software and systems to identify the root cause of the issue
Experience working with real-time systems, large-scale scalable software architectures, and large datasets
Some kind of experience in: robot navigation, machine learning, optimization, computational geometry, graph search, optimal control and estimation
Background in hybrid systems, graph theory, and multi-agent behavioral modeling
Expertise in large-scale cloud infrastructure, e.g. G-Cloud or AWS
Publications in your field (especially CVPR, ICCV, RSS, ICRA)
Follow us on LinkedIn