Job Description:
• 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:
• 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:
• 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