Lead ML/Perception Engineer

🕒 June 8

🇺🇸 United States – Remote

💵 $235k - $275k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

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May Mobility

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

🚘 Automotive

📦 Logistics

🚗 Transport

Automotive • Logistics • Transport

May Mobility is a pioneer in developing autonomous vehicle technology and transportation solutions. They focus on creating safe, reliable, and accessible public transit options by deploying driverless shuttles in urban settings. Their solutions aim to improve urban mobility, reduce traffic congestion, and provide eco-friendly transportation alternatives. With a strong emphasis on pedestrian and passenger safety, May Mobility's technology integrates seamlessly with existing city infrastructure to offer a new vision of public transportation.

📋 Description

• 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.

🎯 Requirements

• A minimum of 5+ years of industry experience working on real-world robot systems maintaining high-quality industrial-grade code. • Master's degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation. • Demonstrated experience leading or making major architectural decisions for a perception, robotics, or autonomy software stack. • Strong programming skills in C/C++/Python; software development in Linux environments. • Strong experience in ML/DL development with PyTorch/TensorFlow. • Direct experience developing or fine-tuning large-scale multi-modal models (e.g., multi-sensor fusion models, foundation models, including VLM backbones) for real-world perception applications. • Experience working on a combination of several of the following real-time areas: • Computer Vision: object detection, classification, segmentation. • Semantic scene understanding, scene/scenario detection, and open-vocabulary detection. • Perception robustness in degraded or adverse-weather conditions. • Multi-target tracking and sensor fusion. • Extensive experience deploying features/ML/DL models in real-time systems with high accuracy and low latency.

🏖️ Benefits

• Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. • Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available. • Rich retirement benefits, including an immediately vested employer safe harbor match. • Generous paid parental leave as well as a phased return to work. • Flexible vacation policy in addition to paid company holidays. • Total Wellness Program providing numerous resources for overall wellbeing

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