A complete application in a minute
Tailored resume and cover letter, ready to send.
May Mobility in Ann Arbor, MI, seeks an Engineering Manager for Prediction within the Behavior team to steer trajectory and intent prediction systems. You will lead a team of engineers bridging ML and robotics architectures to build multi-agent prediction capabilities for the MPDM platform.
You will partner across autonomy, infrastructure and remote operations, drive architectural roadmaps, enforce code quality, and mentor talent while delivering on high-uncertainty projects in a hybrid work
May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think.
Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We're building the world's best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we've given more than 500,000 autonomous rides to real people around the globe. And we're just getting started. We're hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us.
As the Engineering Manager for Prediction within the Behavior team, you will drive the strategic direction and execution of our trajectory and intent prediction systems. Leading a team of specialized engineers, you will bridge machine learning and classical robotics architectures to build multi-agent prediction capabilities for our Multi-Policy Decision Making (MPDM) platform. In this role, you will partner cross-functionally across autonomy, infrastructure, and remote operations to ensure robust safety integration, technical excellence, and scalable talent development.
Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:
Hybrid employees work remotely from their home or alternative work space as well as from one of our offices or sites at an agreed upon cadence set by their leader and based on the nature of their role. _ number of days per week/month or as otherwise agreed to with manager (job function- job dependent) 2 to 3 days per week or 8 days per month in office. Weekly 1-4 days per week
Remote employees work primarily from home or an alternative work space.