Lead Machine Learning Engineer – Localization

May Mobility

Lead ML Engineer architecting production localization and state-estimation systems for May Mobility’s autonomous vehicles. Building robust computer-vision, LiDAR, and radar intelligence for safer, scalable autonomous transit.

Posted 8/4/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $235,000 - $285,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine learning and deep learning models for computer vision and localization, with a strong focus on architecture design, data strategy, and performance evaluation. Proven ability to lead cross-functional teams and mentor engineers while driving technical roadmaps and feature development.

Highest-signal resume keywords

Ph.D. Or Master’s Degree In Computer Science7+ Years Of Industry Experience In ML/DL ModelsExpertise In Computer Vision FoundationsProficient In PyTorch Or TensorFlowStrong Programming Skills In Python And C++

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningComputer VisionLocalizationNeural Architecture DesignData CurationFeature ExtractionQuantizationPruning3D Reconstruction

Soft Skills

LeadershipMentorshipCross-Functional CollaborationTechnical Resolution

Tools & Technologies

PyTorchTensorFlowLinuxLiDARRadarSynthetic Data Generation

Industry Keywords

Localization Machine LearningVision/Fusion Foundation ModelsActive Learning PipelinesOperational Design DomainsFailure-Mode Criteria

Tech Stack

Tools & technologies

LinuxPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Architect and drive the technical roadmap for a production-grade localization machine learning stack spanning map and sparse landmark-based localization using vision, LiDAR, and radar
Lead research, design, training, and validation of neural architectures for detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction
Drive major feature development from inception to deployment, including architecture design, code reviews, automated testing, mentorship, and technical resolution
Own the end-to-end data strategy, including data curation, auto-labeling, synthetic data, and active learning pipelines
Develop metrics and evaluation frameworks for localization performance and system reliability across diverse Operational Design Domains
Define and validate failure-mode and degradation criteria, safety-case coverage, and graceful fallback behavior
Evaluate and integrate multimodal localization and vision/fusion foundation-model techniques into production solutions
Drive cross-functional alignment and translate autonomy goals into software and system requirements

Requirements

What you’ll need

Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field with a strong mathematical and engineering foundation
7+ years of industry experience developing and deploying ML/DL models for computer vision or localization at scale
Deep expertise in computer vision foundations, including object detection, classification, segmentation, tracking, depth estimation, 3D reconstruction, and feature detection/description
Experience with vectorized landmark and feature detection networks, BEV-based scene representation, and temporal modeling
Knowledge of self-supervised/semi-supervised learning, open-vocabulary detection, and vision/fusion Foundation Models
Experience with feature extraction and/or fusion from imagery, LiDAR, and/or radar
Expertise in ML/DL development using PyTorch or TensorFlow
Experience with synthetic data generation, large-scale dataset handling, data curation, and active learning strategies
Strong programming skills in Python and/or C++ with modular software design and Linux-based development
Expertise in ML optimization for real-time products with limited compute, such as quantization and pruning of large transformer models
Proven leadership in technical roadmaps, mentoring engineers, and measurable improvements in model performance and system reliability

Benefits

Comp & perks

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