Job Summary

May’s Senior Engineers are front line problem solvers that get things done. They have the initiative, experience, and technical skill to be able to solve complex technical challenges independently. Confidence backed by knowledge and experience is a must.

As a Senior Autonomy Engineer on the Mapping & Localization team, you will architect solutions for the complex challenges in vehicle autonomy. You will lead the design of future May systems, ensuring our state estimation, localization, and spatial awareness capabilities remain world-class. By solving the system’s most difficult technical hurdles, you will ensure our localization stack delivers the high-confidence data essential for safe operation across diverse and scaling Operational Design Domains (ODDs).

You are responsible for the integrated functioning of the autonomy system. You will interact with sensor hardware, middleware, the autonomy software stack, and compute platforms. You will drive forward architectural design through collaboration across engineering groups and create the validation tooling to prove the system is functioning correctly. You will be a go-to person for understanding how new features integrate, predicting system failure modes, and evolving the stack to be more effective and efficient.

As a leader, you will set an example of initiative, data-driven decision making, design, and trouble-shooting. You will also guide and mentor more junior autonomy engineers so that they can work more effectively with May’s systems. This position reports to the Senior Manager, Autonomy Mapping & Localization.

Essential Responsibilities

• Design, implement, test, and optimize state-of-the-art localization software and systems that maintain high confidence in challenging urban, suburban, and rural scenarios, including GPS-denied urban canyons, foliage, and areas with high moving agent density.
• Lead and participate in team code quality initiatives, including comprehensive design and code reviews.
• Take initiative to understand every aspect of the May vehicle architecture - hardware, software, networking, configurations - all of it.
• Take initiative to find and permanently solve challenging system level issues caused by the interplay between different software and hardware components.
• Troubleshoot and support solutions to challenging field issues.
• Collaborate and lead system-wide improvements when working with other teams without having direct ownership or management responsibility.
• Design, build, and maintain the May autonomy system architecture and cross functional autonomy components.
• Assess and develop approaches that improve performance in a variety of ways (e.g. CPU performance, memory usage, disk usage, network usage).
• Assess and improve system robustness to systematic stochastic and transient issues that impact autonomous vehicle performance.
• Support other autonomy engineers in designing and integrating their components with the full May system.

Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

Required

• Minimum of 5 years of industry experience in autonomous robotics engineering, with a heavy focus on State Estimation, Localization, or SLAM.
• Strong programming skills in C/C++
• Experience taking components and systems from initial research/algorithm design through the full product lifecycle.
• Demonstrated strong troubleshooting and analytic skills at the system and subsystem level.
• Strong background in probabilistic robotics, multi-modal sensor fusion, and sensor calibration.
• Demonstrated ability to communicate effectively and clearly about complex system behaviors, structures, and issues. Ability to explain why a localization module failed in a specific scenario to both a technical peer and a non-technical stakeholder.
• Bachelor's degree in Robotics, Computer Science, Computer Engineering, Electrical Engineering or an applied engineering field.

Desirable

• 10+ years of experience in autonomous robotic systems
• Hands-on experience with factor graph libraries (GTSAM, Ceres, or g2o).
• Experience with autonomous cars, trucks, or similar vehicles.
• A masters or PhD degree in Robotics, Computer Science, Computer Engineering, Electrical Engineering or an applied engineering field.
• Previous experience in a startup or high performance research and development group with an emphasis on delivery
• Experience leading a technical project or mentoring junior engineers (even in a non-managerial capacity).

Physical Requirements

• Standard office working conditions which includes but is not limited to:
• Prolonged sitting
• Prolonged standing
• Prolonged computer use

Travel required? - Minimal: 1%-10%