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May Mobility

Autonomous vehicle mobility solutions for cities

Lead ML/Perception Engineer

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeRemote in USA$235k - $275k

About the Job

Requirements

  • A minimum of 5+ years of industry experience working on real-world robot systems while maintaining high-quality industrial-grade code.
  • A master's degree in Robotics, Computer Science, Computer Engineering, or a field requiring a strong mathematical and/or engineering foundation, or comparable knowledge or experience.
  • Demonstrated experience leading or making major architectural decisions for a perception, robotics, or autonomy software stack.
  • Strong programming skills in C, C++, and Python, and software development experience in Linux environments.
  • Strong experience in machine learning and deep learning development with PyTorch or TensorFlow.
  • Direct experience developing or fine-tuning large-scale multimodal models, such as multi-sensor fusion models and foundation models including vision-language model backbones, for real-world perception applications.
  • Experience in a combination of several real-time areas: computer vision (object detection, classification, and segmentation); semantic scene understanding, scene/scenario detection, and open-vocabulary detection; perception robustness in degraded or adverse-weather conditions; and multi-target tracking and sensor fusion.
  • Extensive experience deploying features or machine learning/deep learning models in real-time systems with high accuracy and low latency.
  • Ability to architect and evolve large-scale perception or autonomy systems while balancing performance, latency, safety, and long-term maintainability.
  • Strong grasp of perception robustness and reliability engineering, including degraded-sensor operation, adverse-weather handling, fault detection, and graceful degradation.
  • Experience with scene/scenario understanding and runtime activation logic, such as context classification, operational design domain monitoring, and behavior triggering.
  • Familiarity with the machine learning development cycle, deployment, and optimization.
  • Deep understanding of data pipelines, data balancing, data mining, and data-driven performance improvement.
  • Knowledge of multimodal learning techniques, including contrastive learning and prompt engineering for zero-shot visual recognition.
  • Deep understanding of testing frameworks and workflows.
  • Excellent attention to detail and rigorous testing methodology.
  • Exceptional written and verbal communication skills and team-leading abilities.
  • Ability to perform prolonged sitting, prolonged standing, and prolonged computer use under standard office working conditions.

Responsibilities

  • 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 or scenario and triggering appropriate perception behaviors and operational design domain logic at runtime.
  • Improve perception robustness under sensor 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 or occlusion.
  • Design, implement, and test state-of-the-art perception features on schedule using high-quality, industrial-grade production code.
  • Integrate large-scale multimodal models, including vision-language models and large language models, 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 machine learning pipelines, specifically focused on multimodal data alignment for training foundation models.

Desired Qualifications

  • Experience developing all-weather or adverse-condition perception, sensor degradation modeling, fault detection, and graceful-degradation strategies for safety-critical systems.
  • Experience with scene/scenario classification, operational design domain monitoring, and runtime capability activation in autonomous systems.
  • Experience re-architecting or migrating large legacy perception systems to modern, scalable frameworks.
  • Experience utilizing large-scale multimodal models for long-tail edge-case detection and explainable artificial intelligence in autonomous systems.
  • Familiarity with synthetic data in machine learning system development.
  • Familiarity with reinforcement learning for machine learning systems.
  • Familiarity with machine learning/deep learning optimization on real-time products with limited compute resources, such as quantization of large transformer models.
  • A strong background demonstrated through high-quality capability deliveries to robots working in the field.

About the Company

May Mobility

Autonomous vehicle mobility solutions for cities

May Mobility builds autonomous mobility solutions by partnering with cities and businesses to offer self-driving passenger transportation and related services. Its system relies on on-board, real-time simulations that let the vehicle anticipate and safely respond to a wide range of road scenarios, enabling safe navigation in urban environments. Unlike many competitors that rely on external testing or staged environments, May Mobility emphasizes safety by continuously simulating potential situations on board to prevent risky maneuvers. The company differentiates itself through its city-focused partnerships and its emphasis on improving urban mobility, safety, and environmental impact. Its goal is to make cities more accessible and visually appealing by transforming how people move, using autonomous vehicles as a practical, scalable mobility solution.

Company size
201-500
Company stage
IPO
Headquarters
Ann Arbor, MI
Founded
2017

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