Principal Engineer, Team Lead - Localization and Mapping

Position Overview

• Location Type: Not specified
• Employment Type: Not specified (likely Full-time)
• Salary: Not specified (estimated range provided)

The Localization Technical Lead Manager (TLM) will lead and manage a team of state estimation engineers, designing and developing cutting-edge systems and software for autonomous driving efforts. This role is critical for driving next-generation localization solutions within the Localization, Mapping and Calibration (LMC) organization. The company is seeking passionate and experienced leaders interested in career growth within a fast-growing autonomous driving technology company.

Responsibilities

• Define and execute localization projects that improve the self-driving vehicles’ capability to safely and comfortably navigate complex Operational Design Domains (ODDs).
• Lead, manage, and grow a team of engineers.
• Drive the strategy and roadmap for next-generation localization solutions.
• Communicate strategies, progress, and challenges to executive leadership.
• Design and lead the implementation of localization solutions leveraging the latest in SLAM/VSLAM, including advancements using Machine Learning (ML).
• Productionize and deploy solutions onto autonomous vehicle fleets.
• Collaborate with mapping, perception, integration, and systems teams to validate and enhance on-road performance.

Requirements

• Education: Masters or PhD in Computer Science, Robotics, or a related technical field; or equivalent industry experience.
• Experience: Extensive experience managing and leading engineers.
• Leadership Skills: Proven leadership skills in executing large, complex technical initiatives.
• Track Record: Proven track record of shipping production software in localization or state estimation.
• Technical Expertise:
  • Deep understanding of SLAM (Simultaneous Localization and Mapping), particularly state-of-the-art visual and visual-inertial SLAM.
  • Fluency in C++ software engineering and algorithm skills in a Unix environment.
  • Advanced knowledge of software engineering principles, including software design, source control management, build processes, code reviews, and testing methods.

Bonus Points

• Experience applying machine learning techniques to SLAM problems.
• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry.

Application Instructions

Not specified. Applicants should likely apply through the company's career website.

Company Information

Not specified. Further details about the company can be found on their website.