Robotics Engineer II

About the role

Robotics Engineer II: Shaping Autonomous Mobility

May Mobility is pioneering a transformation in urban environments through advanced autonomous systems. Headquartered in Ann Arbor, Michigan, the company creates technologies designed to enhance safety, promote sustainability, and improve accessibility for communities worldwide. The core of this mission is the Multi-Policy Decision Making (MPDM) platform, a sophisticated system that dictates how vehicles interpret and interact with dynamic surroundings. This innovation allows the fleet to operate with a level of cognitive decision-making that prioritizes passenger safety and seamless integration into existing transit ecosystems. Since its establishment in 2017, May Mobility has provided over 500,000 autonomous rides to passengers, demonstrating a proven track record in real-world deployment. The company continues to expand its reach, seeking driven individuals to solve complex challenges and build the future of transportation.

This position represents a critical role within the engineering organization, responsible for the full lifecycle of on-vehicle autonomy software. The successful candidate will directly influence the intelligence of the fleet, ensuring vehicles operate with predictable and reliable behavior. The work has a direct impact on the rider experience, contributing to safer streets and more efficient public transit links. This is an opportunity to own technical decisions that shape how autonomous vehicles learn and perform in demanding environments.

Position Responsibilities

The Robotics Engineer II will be central to defining and maintaining the autonomy stack. This involves creating robust data strategies that identify and correct model weaknesses before they affect riders. You will be responsible for developing internal tools that provide transparency into vehicle performance, enabling the support teams to diagnose issues quickly. Another key duty is managing the execution of on-road validation campaigns, ensuring software updates meet rigorous safety standards under diverse conditions. When issues arise in commercial service, you will lead the investigation to determine if the root cause lies within the perception system, the planning algorithms, or the interaction between modules. The role also demands constant refinement of the software stack to meet strict latency and reliability targets, ensuring the vehicle response remains instantaneous and dependable. Finally, you will construct analytical pipelines that translate raw fleet data into actionable intelligence for product and engineering leadership.

Qualifications and Experience

Candidates for this position must possess a strong foundation in robotics software development, specifically for physical, deployed systems. A Bachelor's degree in Robotics, Computer Science, Computer Engineering, or a related technical discipline is required. This educational background should provide a deep understanding of mathematical principles and engineering concepts. A fundamental comprehension of machine learning is essential, including how models are trained and how data selection influences outcomes. Practical knowledge of sensor suites-including lidar, cameras, and radar-is necessary to understand how perception inputs are generated and processed. Proficiency in programming languages such as C, C++, and Python within a Linux environment is mandatory. Experience with software development best practices, including memory management and networking, is expected. Familiarity with version control and debugging tools is crucial for maintaining code quality and stability.

Preferred Qualifications

While not mandatory, additional expertise can significantly impact the effectiveness in this role. Experience with the concepts used in autonomous driving perception, planning, and decision-making is highly valuable. A background in deploying machine learning models onto embedded hardware with limited resources is a distinct advantage. Knowledge of high-performance computing techniques, such as CUDA, and methods for optimizing GPU utilization is also desirable. Understanding advanced data curation methods, including techniques for handling challenging scenarios or balancing data classes, is viewed favorably. The ability to define and track key performance indicators for AV models is critical for guiding long-term strategic improvements. Experience in building large-scale training and evaluation pipelines, capable of handling massive datasets or complex model architectures, is a key asset for success in this position.

Compensation and Work Details

This is a full-time position based in Ann Arbor, Michigan. The compensation package for this role ranges from $136,800 to $179,900 annually, reflecting the level of responsibility and technical expertise required. The role involves minimal travel, estimated at 1% to 10% of time. Standard office working conditions apply, which may include periods of prolonged sitting, standing, or computer use. Candidates are encouraged to review the official application page for specific details regarding logistics and requirements before proceeding.