Autonomy Lifecycle Engineer II

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. Job Summary  We are looking for an Autonomy Lifecycle Engineer to own the connection between deployed autonomous vehicle performance and engineering development. This role is critical in closing the loop between real-world operations and software development by translating data into actionable insights that drive system improvements. You will help bridge autonomy software development with real-world deployment and data analytics, ensuring that new capabilities transition into safe, reliable, and scalable service across May Mobility’s operational sites. This is a hybrid role based in Ann Arbor, Michigan , with occasional travel to operational sites.   Essential Responsibilities Own performance analysis of deployed autonomous vehicle fleets across commercial and test operations Define, develop, and maintain key performance indicators (KPIs) to measure system performance and operational success Build and maintain data pipelines, tools and dashboards to process and analyze vehicle and operational data Analyze real-world vehicle behavior to identify trends, anomalies, and systemic issues Translate data insights into clear problem statements and prioritized inputs for engineering teams Drive a closed-loop lifecycle process connecting deployed software, vehicle performance and engineering improvements Partner with engineering teams (perception, prediction, behavior, platform) to influence priorities and upcoming software releases based on real-world impact Collaborate with product and roadmap teams to ensure field performance insights are reflected in feature prioritization Work closely with Technical Project Managers (TPMs) to provide performance snapshots, status updates and data-driven support for customer-facing activities Establish and maintain processes to align stakeholders across engineering, product, operations, and deployment teams Communicate performance insights and recommendations clearly across technical and non-technical audiences Create and maintain performance and issue metrics, ensure broad availability and accessibility of relevant data and translate analytical insights into clear, actionable and stakeholder-ready formats such as dashboards, reports and performance summaries   Skills and Abilities Success in this role typically requires the following competencies: Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science or a related field Experience in autonomous systems, robotics or complex software/hardware systems Strong analytical and problem-solving skills with experience working on large datasets Experience with data analysis tools and programming languages (e.g., Python, SQL) Experience building dashboards, metrics and data processing pipelines Ability to translate complex data into actionable insights and communicate effectively across teams and organizational levels Experience working cross-functionally with engineering, product, and operations teams Comfortable operating in a fast-paced, dynamic environment with evolving processes Qualifications and Experience Required Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Robotics or a related technical field 5–7+ years of experience in autonomous systems, robotics, mobility, or other complex software/hardware systems, with a strong focus on real-world system performance, operations or lifecycle analysis Proven experience owning end-to-end problem spaces, from data analysis and issue identification through to influencing engineering prioritization and driving resolution Strong expertise in data analysis and engineering, including working with large-scale datasets, telemetry or vehicle/system logs (e.g., Python, SQL, or similar tools) Experience building and scaling metrics frameworks (KPIs), dashboards and data pipelines to monitor and improve system performance Demonstrated ability to translate complex data into actionable insights and