Principal Engineer - Behaviors

Position Overview

• Location Type: Remote (within the United States)
• Employment Type: Full-time
• Salary: Not specified

This opportunity allows you to work with world-class ML engineers and research scientists focused on making self-driving vehicles a reality and creating positive social impact. You'll be part of the Behaviors team, responsible for the tech stack that perceives dynamic scenarios and predicts the future behavior of agents around robo-taxis. The role supports remote work within the US with occasional travel.

Responsibilities

• Drive project-level impact to make autonomous vehicles operate at superhuman capabilities for comfortable, safe driving.
• Define and influence the direction of the team, organization, and/or department.
• Advise leaders on technology problems and solutions.
• Connect and drive business impact through technology solutions.
• Formulate problems, architect solutions, and design processes.
• Prototype, evaluate, implement, and iterate on solutions.
• Pioneer research into state-of-the-art solutions and systems for autonomous vehicles.
• Productionize and deploy solutions onto autonomous vehicle fleets.
• Mentor and grow junior and experienced engineers and researchers.
• Help create and reinforce a culture of inclusion, innovation, and excellence.

Requirements

• Education: BA, Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, or a related field; or equivalent industry experience.
• Machine Learning Knowledge: In-depth understanding of common Machine Learning and Deep Learning algorithms.
• Neural Network Experience: Experience designing, training, and analyzing neural networks for at least one of the following applications:
  • Object detection
  • Semantic/instance segmentation
  • Visual classification
  • Motion/gesture recognition
  • Sensor fusion
  • Multitask learning
  • Motion prediction
  • Multi-object tracking
• Software Engineering Skills: Advanced knowledge of software engineering principles, including:
  • Software design
  • Source control management
  • Build processes
  • Code reviews
  • Testing methods
• Programming Skills: Fluency in Python, including standard scientific computing libraries and Python bindings development experience.
• Deep Learning Frameworks: Experience with PyTorch or other deep learning frameworks.
• Data Analysis: Experience working with large data sets and deriving insights from data.
• Leadership & Execution: Effectiveness at leading and executing large, complex technical initiatives.

Bonus Points

• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.).
• PhD in machine learning, computer vision, or robotics vision.
• Experience working on autonomous vehicles or related fields.
• Experience in deploying models into real-world environments.
• Strong programming skills.