Technical Lead - Planning and Controls

Gatik

Palo Alto, CA, USA

Full time

Aug 10

This job is no longer accepting applications.

Gatik is leading the way in autonomous middle-mile delivery by developing a safe, efficient, autonomous delivery solution that addresses real pain points for the retail industry. Operating on fixed, predetermined routes, we are the first company to develop and deploy light/medium duty autonomous box trucks. 

Founded in 2017, 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. Gatik’s autonomous vehicles have been operating in North America with multiple Fortune 500 retail partners including Walmart, Loblaws, and others yet to be announced publicly. These partnerships are a first in the AV industry: this kind of middle-mile integration with major retailers has never been done before, marking the first-ever deployment of a hub-and-spoke AV delivery model.

We are seeking talented engineers to work on a mix of planning and control problems and lead efforts to improve how our vehicles act and react in complex and nuanced situations. Through effective collaboration with established teams, you will help build motion planning and decision-making systems and mature new products all the way through to production. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

Responsibilities

  • Build and improve motion planning and decision-making systems for the self-driving vehicles, ensuring that the behavior of our vehicles is safe, smooth, and predictable to other road users
  • 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
  • Model vehicle and controller dynamics and use these models to characterize and accelerate controller improvements
  • Guide all technical aspects of development, including technical requirements definition, design, implementation, unit testing, and integration
  • Develop efficient Deep Learning architectures that run in real-time or other resource constrained setting

Qualifications

  • M.S. or Ph.D degree in CS, Robotics or related field
  • Strong C++ programming and software design skills 
  • Expertise implementing autonomy solutions and deploying on real-world systems
  • Extensive experience working in container based technologies like Docker
  • Strong background in data structures and algorithms
  • Familiarity with modern planning approaches including randomized search methods and trajectory optimization and modern model predictive control and other advanced control techniques
  • Experience with emerging deep learning based motion planning approaches (LSTMs, Deep Reinforcement Learning, Deep Q-learning, etc)
  • Significant experience with project and program management using tools such as JIRA, Confluence etc
  • Experience with safety system architecture and design principles
  • Strong problem-solving skills – ability to troubleshoot complex software and systems to identify the root cause of the issue

Bonus Points

  • Expertise in large-scale cloud infrastructure, e.g. G-Cloud or AWS
  • Experience with ROS/ROS2 or other middleware systems
  • Experience working with real-time systems, large-scale scalable software architectures, and large datasets
  • Understanding of test and verification methodologies for automotive software
  • Experience in applying ML for control or planning problems (e.g. Imitation Learning, Behavior Prediction, Reinforcement Learning)
  • Experience with C++ build systems, such as bazel and CMake
  • Solid technical foundation in CPU and GPU architectures, containers and numeric libraries
  • Background in hybrid systems, graph theory, and multi-agent behavioral modeling
  • Publications in your field (especially CVPR, ICCV, RSS, ICRA)

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Gatik

Autonomous Delivery Network for the Middle Mile

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