May Mobility

Program Manager

• Manage program timelines and track status of deliverables from the Product Definition until the OK to Launch phase for one or multiple Autonomous Vehicle platforms
• Identify dependencies across tasks and program teams to ensure continuous alignment
• Track risk and manage mitigation plans
• Communicate with development partners and customers to align program plans to escalate vehicle issues
• Develop and manage program budgets, tracking expenditures across the full program lifecycle to ensure financial targets are met and variances are proactively addressed
• Lead cross-functional teams to define, track, and achieve bill of material cost targets in support of growth objectives
• Implement and manage change when necessary to meet desired outputs
• Present to stakeholders reports on progress as well as problems and solutions
• Champion prioritization of safety and quality
• Support continuous improvement of the vehicle development and program management process
• Develop and leverage relationships across functions to ensure clear communication and seamless follow-through

Senior Program Manager

Machine Learning Engineer

• Design, implement and own ML metrics and evaluation pipelines spanning offline model evaluation, simulation and on-road performance.
• Build and maintain test, regression and hillclimbing suites that gate model and stack releases, including automated triage of regressions to root cause.
• Drive model improvement through loss analysis, error mining, and data balancing/curation strategies for training and evaluation sets.

Machine Learning Engineer II – Autonomous Driving Performance Evaluation

• Deploy and Optimize Machine Learning model architectures across May’s Autonomous Driving training and inference stacks.
• Own the model-compilation and deployment pipeline end-to-end.
• Establish and defend latency/throughput budgets across the AV stack, including profiling, regression and integrity tests.

Machine Learning Engineer II – Autonomous Driving, Inference Runtime

Engineer

• Work independently with cross-functional teams to develop software and system requirements.
• Lead major architectural updates to the perception stack, including system-level design, modularization, and migration strategies that improve scalability, latency, and maintainability across the fleet.
• Design, develop, and own scene detection and activation capabilities, classifying the operating scene/scenario and triggering the appropriate perception behaviors and operational design domain (ODD) logic at runtime.
• Improve perception robustness under degradation and adverse weather, including sensor fault detection, health monitoring, graceful degradation, and fallback strategies for rain, snow, fog, glare, low-light, and sensor soiling/occlusion conditions.
• Design, implement, and test state-of-the-art perception features on time with high quality, industrial-grade production code.
• Integrate large-scale multi-modal models (including but not limited to VLMs and LLMs) into the perception stack to improve semantic scene understanding and reasoning.
• Track and trend technical performance of perception in the field.
• Lead major feature development including feature design, code reviews, issue diagnosis, and resolution.
• Lead extensive testing to validate features and satisfy release schedules.
• Lead development related to data, development, and ML pipelines, specifically focused on multimodal data alignment for training foundation models.

Lead ML/Perception Engineer

Data Scientist

• Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform that supports them; translate that strategy into a 12–24 month roadmap with measurable milestones.
• Lead, grow, and develop a team of senior data scientists, ML engineers, and front-line managers; recruit from a small expert pool, calibrate the bar, and build a hiring brand that allows May Mobility to win against AV, robotics, and AI competitors.
• Partner with Engineering, Product, Safety, and Operations leaders to define release criteria, performance metrics, and ODD-expansion gates; use data to make the business case for what we deploy, where, and when.
• Drive ML and analytics applications end-to-end: dataset curation, scenario coverage, modeling, offboard evaluation, productionization, and continuous monitoring of fleet performance in the wild.
• Establish measurement and experimentation standards across the company — including before/after analyses for stack changes, A/B-style comparisons in simulation, and statistically credible reporting on real-world incidents.
• Lead team-wide quality activities including design and code reviews; hold the bar on engineering rigor for production data science systems.
• Track and trend technical performance of the autonomy stack in the field; surface root causes, prioritize fixes with engineering, and represent fleet-data findings to executives, regulators, and partners.
• Provide technical guidance to Engineering and Operations leaders on issue diagnosis, resolution, and the ML changes most likely to move our key safety and service metrics.
• Represent May Mobility's data science work externally where appropriate — through publications, conference talks, partner reviews, and recruiting.

Director, Data Science

• Design, implement, and test-state-of-the-art robotics software in C/C++ to enable comfortable and safe behavior and control for Autonomous Vehicles
• Lead and participate in team code quality activities including design and code reviews
• Provide technical guidance to Technical Support Team on issue diagnosis and resolution
• Coordinate with cross functional teams to develop software and system requirements for Autonomous Vehicle behavior and controls subsystems
• Collaborate with data science team members to design and implement metrics capturing key performance indicators of Autonomous Vehicle subsystems
• Develop unit and simulation tests to validate vehicle performance across target operational domains
• Coordinate and execute on-vehicle tests to validate performance of Autonomous Vehicle software in real-world scenarios
• Diagnose and root-cause issues reported by commercial operations through the May Field Response process
• Develop tools and visualizations to enable support engineers to analyze performance of behavior and control subsystems from field data

Lead Autonomy Behavior Engineer

Executive Assistant

• Anticipate the Exec’s needs and act proactively to address them, including preparing meeting materials, briefing documents, and agenda items in advance.
• Monitor deadlines and follow up on action items, ensuring timely completion of tasks and facilitating effective decision-making.
• Ensure agendas and necessary documents / materials are provided 24 hours prior to a scheduled meeting 100% of the time
• Proactively manage the Execs calendar, including scheduling, prioritizing appointments, and coordinating all internal and external meetings.
• Attend meetings as needed, with a focus on driving organizational efficiency
• Manage travel logistics to include, flights, hotel, car rental, reimbursements, etc.
• Work closely with administrative staff and Chief of Staff to continually streamline and simplify meetings and team workflow across May
• Supporting multiple Senior Executive staff
• Answers general calls and emails for the main office and greets visitors.
• Ensure the Executive team is kept up to date on relevant news and information by sending announcements, newsletters, etc.
• Provide support for across teams such as marketing, sales, people, operations for special projects
• Plan company events including social, professional development, and business development
• Manage, process, and review expenses for the executives, and their team’s direct reports as needed
• Partner consistently and efficiently with other members of the EA team and cross-functional partners across the org
• Schedule internal and external meetings with a variety of cross-functional partners
• Coordinate meetings across time zones
• Respond and take action on a high volume of slacks and emails with urgency and professionalism
• Map out and circulate meeting agendas, facilitate meetings, and manage post-meeting follow-ups
• Other duties as assigned

Senior Executive Assistant

DevOps Engineer

• Release ownership and execution across major autonomy releases, incremental/performance releases, and hotfix/safety patches
• Manage branching strategy, versioning, and release cut processes
• Drive release readiness and go/no-go decisions in partnership with cross-functional teams
• Design, build, and maintain internal tooling to support:
• Release readiness dashboards and automated health checks
• Simulation corpus integration and regression tracking
• Release metrics collection, reporting, and visualization
• Automated validation signal aggregation across sim, HIL, and on-road testing
• Investigate and resolve complex issues arising from software/hardware interactions, distributed systems behavior, and on-vehicle vs. simulation discrepancies
• Develop working understanding of sensor stack, middleware, autonomy stack, compute platforms, networking, and vehicle configurations
• Enforce stage-gated release framework: Feature Complete → Code Freeze → Validation → Release Candidate
• Integrate and interpret validation signals including simulation corpus results, regression testing, and vehicle testing
• Ensure safety-critical issues are identified, tracked, and gated appropriately
• Identify opportunities to improve system robustness, performance, and scalability — and build tooling to measure and track improvements
• Support autonomy engineers in designing and integrating their components with the full May system
• Contribute to and help maintain the team's knowledge base, runbooks, and release documentation

Autonomy Release Engineer II

Translator

• Architect and lead the development of a production-grade, multimodal localization stack, integrating Cameras, LiDAR, Radar, GNSS, and IMU data to ensure centimeter-level accuracy and high availability.
• Design and implement advanced state estimation frameworks, such as Factor Graphs or sliding-window optimization (e.g., GTSAM, Ceres), optimized for real-time performance and robustness against sensor degradation and across diverse Operational Design Domains (ODDs).
• Own the localization integrity and safety strategy. Develop sophisticated uncertainty estimation and fault detection, isolation, and recovery (FDIR) mechanisms to meet stringent safety requirements.
• Drive technical roadmaps for next-generation localization techniques, including map and sparse landmark-based localization (Vision/LiDAR/Radar), visual-inertial odometry (VIO), and wheel-inertial odometry.
• Lead cross-functional system integration, developing software and system requirements while defining technical interfaces and performance contracts (e.g., state estimation and uncertainty bounds) between Localization and upstream and downstream modules like Perception, Behavior, Policy, and Prediction.
• Establish rigorous evaluation frameworks and metrics for localization performance, including pose accuracy, temporal consistency, and system-level reliability across diverse ODDs.
• Spearhead major feature development including high-level architecture design, code reviews, issue diagnosis, and technical resolution.
• Provide high-level technical mentorship to senior and junior engineers, conducting deep-dive design and code reviews and fostering a culture of engineering excellence and rigorous validation.
• Stay at the research frontier, evaluating and adapting cutting-edge techniques in SLAM, deep-learned localization features, and large-scale map-matching to deliver production-ready solutions.

Staff Autonomy Engineer – Localization

Director

• Lead a multi-disciplinary team across systems, test execution, and safety risk and process/SMS
• Drive the Driver-Out (DO) gated deployment plan with strategic ride-hail partners (Lyft, Uber) — internal gating, partner safety onsites, and recommendation packages for go/no-go decisions
• Own the Safety Case Framework for May's L4 systems, including HARA, FTA, FMEA, and runtime-monitor coverage for the MPDM-based decision-making stack, with ML-aware safety analysis
• Build out and operationalize the Safety Management System (SMS): incident risk assessment process, risk register automation, recall response plan, safety gating test suite, and the Product Safety Competency Register.
• Define safety architecture — partner with Autonomy, Validation, and Hardware to ensure safety-by-construction across future releases (scalable runtime monitoring, ODD enforcement, Driver-Anomaly response systems).
• Execute on May's L4 Japan compliance plan — partner with the Systems & Japan Programs Manager and the Japan Regulatory Safety Engineer on partner engagement and bilingual regulator response cadences.
• Co-lead strategic partner safety onsites (e.g., Uber Safety Onsite cadence) with the VP, Safety & Validation; own the technical narrative in OEM, ride-hail, and regulator forums.
• Hire and onboard the open safety roles and develop existing leaders in the org.

Director, System Safety

• Work closely with senior technologists to train, optimize and evaluate vehicle-oriented Machine Learning models
• Work cross functionally with Perception, Behavior, Integration, Test and Data teams to ensure the highest quality in model performance and deployment

Machine Learning Engineer II

• Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack.
• Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.
• Lead small teams of cross functional Engineers beyond the state of the art.
• Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.

Lead Machine Learning Engineer

IT Support

• Lead the preparation of the corporate risk assessment analysis and work with management and those charged with governance in planning audits
• Enhance the company’s control framework by contemplating documentation available to date and establishing and updating internal controls as a result of the risk assessment and business knowledge obtained within this role
• Support the execution of risk assessments for business and product areas, analyze gaps identified and recommend remediation actions for risk gaps
• Define audit scope and design control testing steps to evaluate the adequacy of the control designs and operating effectiveness
• Effectively partner with finance, legal, and cross functional stakeholders to ensure completion of remediation activities agreed upon during audit projects
• Provide guidance to all departments as to control and process best practices and assist with enhancing and establishing policies, implementation of new systems or applications incorporating responses to audit finding or recommendations
• Participate in cross-functional meetings to ensure regulatory and risk issues are properly identified and managed in new and existing product and services
• Lead trainings internally to increase awareness of internal controls
• Coordinate internal audit work performed by third-party firms
• Collaborate and provide recommendations on the future vision of the internal audit function, which includes considerations of resourcing, internal audit methods, and technology enablement
• Leads coordination with the external audit team in supporting the documentation required for internal controls for the annual audit

Internal Audit Manager

• Lead the research, design, architecture, training and validation of advanced neural networks for vectorized mapping (e.g., MapTR), multi-camera BEV transformers, and multimodal fusion models to extract and model lane and route networks for both high-fidelity offline pipelines and real-time online mapping.
• Architect, design, and implement a production-grade lane and route network mapping stack, ensuring high-performance integration with upstream and downstream modules like Perception, Behavior, Policy, and Prediction.
• Drive major feature development from inception to deployment. This includes high-level architecture design, rigorous code reviews, automated testing, mentorship of junior engineers, and technical resolution.
• Own the end-to-end data strategy for the mapping domain, specifically focusing on lane and route networks. You will define data curation, auto-labeling, synthetic data, and active learning pipelines to capture and resolve long-tail scenarios.
• Develop robust metrics and evaluation frameworks for lane and route network accuracy, temporal consistency, and scaling across diverse Operational Design Domains (ODDs).
• Work independently with cross-functional teams to translate complex autonomy goals into clear software and system requirements.
• Collaborate with ML and Autonomy engineers to ensure the seamless deployment and validation of mapping features to the vehicle fleet.
• Stay at the research frontier by evaluating, adapting, and innovating cutting-edge techniques, including online vectorized HD map construction, end-to-end mapping models, and vision/fusion Foundation Models to deliver production-ready solutions.

Lead ML Engineer – Lane & Route Networking Mapping

General Counsel

• Draft, review, and negotiate a range of commercial and supplier agreements, including hardware supply, software licensing, services, joint development, and partnership agreements, while developing and maintaining playbooks, templates, and negotiation guidelines for use across the legal team
• Design, implement, and maintain compliance programs and policies covering areas such as data privacy, safety, regulatory obligations, and corporate governance
• Provide day-to-day legal counsel to cross-functional teams including engineering, operations, business development, government affairs, marketing, and human resources
• Advise on regulatory matters related to autonomous vehicle testing, deployment, and commercialization at the federal, state, and local levels
• Support the management of outside counsel and coordinate with external advisors on specialized matters including litigation, IP, and regulatory filings
• Monitor and analyze evolving laws and regulations affecting autonomous vehicles, transportation, data privacy, and employment, and summarize business implications to leadership
• Develop and deliver training programs on legal compliance, contracting best practices, and risk management for business teams
• Assist with corporate transactions, equity matters, and board-related activities as needed