Jobs at May Mobility

Supports on-site configuration, deployment, troubleshooting, and demonstrations of autonomous vehicle technology. Scouts locations, resolves traffic-environment challenges, represents the company to customers and the public, and collaborates with engineers to expand system capabilities and improve rider experiences. The role requires hands-on hardware and/or software experience, bilingual English and Japanese communication, vehicle operation, and frequent travel.

Leads integration testing across an autonomous vehicle software stack, coordinating deliveries, maintaining integration branches, and managing CI/CD pipelines. Designs simulation campaigns, conducts on-vehicle validation, tracks system performance metrics, diagnoses regressions, and coordinates root-cause resolution across perception, planning, and controls teams. The role also contributes software fixes and communicates system health through engineering reports. This is a hybrid Ann Arbor position with travel up to 25%.

Leads the engineering team responsible for autonomous-vehicle trajectory and intent prediction systems. The role guides machine learning and classical robotics architecture, integrates safety metrics and operational design requirements, manages roadmaps and cross-functional delivery, supports root-cause analysis, enforces engineering quality, and develops technical talent. It also requires dashboard and KPI ownership, fleet-data analysis, and collaboration across autonomy, infrastructure, perception, modeling, and remote operations teams.

Leads hardware-in-the-loop and vehicle-level integration testing for autonomous systems. Develops test plans, automated test suites, fault-injection scenarios, and performance analyses; tests sensors, compute modules, vehicle communications, and safety-critical software. Integrates test workflows with AWS, documents anomalies, validates edge cases, and collaborates with software, hardware, systems, and autonomy engineering teams while mentoring team members.

Leads supply chain strategy and operations, including procurement, sourcing, inventory, logistics, supplier relationships, contract negotiation, and cost reduction. Manages purchasing and supply chain teams, oversees shipping and receiving, maintains ERP inventory accuracy, supports manufacturing design reviews, and ensures purchasing compliance. Partners with engineering, finance, accounting, and suppliers to improve quality, availability, scalability, and operational performance.

Integrate hardware, software, and vehicle systems for autonomous driving platforms. Own requirements development, systems integration, validation, verification metrics, FMEA, and cross-functional trade-off resolution. Collaborate with system architects, controls teams, test and validation groups, and OEM partners to ensure platform requirements and performance targets are met. Evaluate regulatory requirements, improve engineering processes, and maintain polished specifications throughout the development lifecycle.

Lead autonomous vehicle deployments at new sites, configuring systems, resolving location-specific technical challenges, representing the company to customers, demonstrating autonomous technology, collaborating on system improvements, and mentoring junior engineers. The role requires hands-on hardware and software experience, Linux proficiency, programming knowledge, autonomous vehicle or mobile robotics experience, vehicle operation, and frequent travel up to 50%.

Leads full-stack and infrastructure engineering teams responsible for simulation platform architecture, cloud infrastructure, container orchestration, databases, APIs, frontend tools, reliability, observability, and cost efficiency. Owns the strategic roadmap for scenario management, run orchestration, taxonomy, and results analytics. Recruits and mentors engineers, partners with simulation teams, manages integration interfaces, and delivers scalable infrastructure for massive parallel batch simulations.

Own performance of a real-time autonomous vehicle behavior-planning pipeline, including latency, throughput, memory usage, thread safety, profiling, optimization, concurrency, benchmarking, telemetry, and performance regression prevention. Partner with autonomy teams to design low-overhead C++ interfaces and execution guardrails.

Supports autonomous vehicle fleet operations at site locations by implementing vehicle upfits, debugging electrical and mechanical systems, calibrating sensors, testing features, maintaining mapping assets, performing preventative maintenance, and deploying autonomous technology. The role also acquires vehicle data, documents issues, coordinates resolutions with engineering teams, and ensures safe, comfortable, demo-ready vehicle operation.

Leads technical projects and cross-functional teams solving complex autonomous-driving problems. Responsibilities include analyzing data, clarifying requirements, prioritizing technical work, mitigating risks, tracking project status, and coordinating across autonomy, vehicle engineering, software, product, finance, and operations. The hybrid role is based in Ann Arbor, Michigan, with occasional travel to operational sites.

Leads end-to-end technical release coordination for autonomous vehicle software, aligning engineering, validation, safety, DevOps, deployment, product, and business teams. Owns release readiness, risk and dependency tracking, production incident management, hotfix and commercial release lanes, and remediation through resolution. Establishes closed-loop improvement processes that incorporate incident and root-cause learnings into future planning and validation. Creates program artifacts, communicates technical issues to diverse stakeholders, and drives timely, high-quality delivery.

The Senior Accountant will manage reconciliations, month-end close activities, accruals, journal entries, vendor invoicing, and accounting documentation. The role supports accounts payable, accounts receivable, payroll, inventory and bill-of-materials tracking, financial statements, audits, expense compliance, internal controls, forecasting, reporting, and system implementations. The position also researches accounting treatment under US GAAP and ASC 606, presents findings to management, and collaborates cross-functionally with finance, supply chain, engineering, vendors, and employees.

The Systems Engineer II will support system design and cross-functional engineering efforts, collaborating with test and validation teams to ensure compliance with requirements and specifications.

As a Senior Product Safety Architect, you will define the safety architecture for L4 autonomous systems, ensuring compliance with safety standards and managing risks associated with AI/ML components.

The Senior Systems Engineer will facilitate cross-functional engineering efforts, support system design, and collaborate with Japan's team for autonomous vehicle projects. Responsibilities include technical requirements analysis, testing, and continuous improvement initiatives.

Design, operate, and scale ML data and training pipelines for autonomous driving. Build distributed training, orchestration, CI/CD and infrastructure-as-code; maintain data/metadata stores and tooling to support large-scale model training and evaluation across cloud and cluster environments.

The Senior Data Scientist will develop metrics for evaluating autonomous vehicle performance, analyze data, collaborate across teams, and communicate findings to improve safety and passenger experience.

Train, integrate, test, optimize, and monitor machine learning models and autonomy software on autonomous vehicles. Coordinate real-world vehicle testing, diagnose field issues, design data collection strategies, and develop tools and visualizations for analyzing behavior and control subsystem performance. The role requires robotics software development, sensor interface knowledge, Linux programming, and software debugging expertise.

Design, train, and evaluate advanced machine learning models for autonomous driving, simulation, and ML platforms. Lead small cross-functional engineering teams, establish data and experiment practices for petabyte-scale training, address long-tail model failures, and work with multimodal datasets exceeding 100TB. The role requires commercial robotics experience, mentoring capability, expertise in VLA or generative world models, Python/PyTorch, sensor processing, and potentially edge deployment.