Lead Machine Learning Engineer – Localization

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and lead the technical strategy for a production-level localization machine learning framework that encompasses map and sparse landmark-based localization utilizing vision, LiDAR, and radar technologies.

• Oversee research, design, training, and validation of neural network architectures for tasks including detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction.

• Spearhead significant feature development from concept to implementation, which includes architecture design, code reviews, automated testing, mentorship, and resolving technical issues.

• Take ownership of the comprehensive data strategy, which covers data curation, auto-labeling, synthetic data generation, and active learning pipelines.

• Create metrics and evaluation frameworks to assess localization performance and system reliability across various Operational Design Domains.

• Establish and validate criteria for failure modes and degradation, safety-case coverage, and appropriate fallback behaviors.

• Assess and incorporate multimodal localization and vision/fusion foundation-model methodologies into production systems.

• Facilitate cross-functional collaboration and translate autonomy objectives into software and system specifications.

⛳️ Requirements

• Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a closely related discipline with a robust foundation in mathematics and engineering.

• Over 7 years of professional experience in developing and deploying ML/DL models for computer vision or localization at scale.

• In-depth knowledge of computer vision principles, including object detection, classification, segmentation, tracking, depth estimation, 3D reconstruction, and feature detection/description.

• Familiarity with vectorized landmark and feature detection networks, BEV-based scene representation, and temporal modeling techniques.

• Understanding of self-supervised/semi-supervised learning, open-vocabulary detection, and vision/fusion Foundation Models.

• Experience in feature extraction and/or fusion utilizing imagery, LiDAR, and/or radar data.

• Proficiency in ML/DL development with frameworks such as PyTorch or TensorFlow.

• Background in synthetic data generation, managing large-scale datasets, data curation, and active learning methodologies.

• Strong programming capabilities in Python and/or C++ with an emphasis on modular software design and Linux-based development environments.

• Expertise in ML optimization for real-time applications with constrained computational resources, including quantization and pruning of large transformer models.

• Demonstrated leadership in shaping technical roadmaps, mentoring engineers, and achieving measurable enhancements in model performance and system dependability.

🏝️ Benefits

• Comprehensive healthcare package that includes medical, dental, vision, life, and disability insurance plans.

• Domestic partners who have cohabitated for at least one year are eligible for participation in healthcare plans.

• Health Savings and Flexible Spending Accounts for Healthcare and Dependent Care.

• Robust retirement benefits, featuring an immediately vested employer safe harbor match.

• Generous paid parental leave and a phased return-to-work program.

• Flexible vacation policy.

• Paid company holidays.

• Total Wellness Program offering a variety of resources for overall health and wellbeing.