Machine Learning Engineer developing consumer - facing AI features powered by LLMs at Quora. Collaborating with engineers and optimizing production AI systems for enhanced user engagement.
About the role
- Lead ML Engineer developing neural networks for lane and route networking at May Mobility. Focus on architecture, design, and validation for autonomous technology solutions.
Responsibilities
- Lead the research, design, architecture, training and validation of advanced neural networks for vectorized mapping (e.g., MapTR), multi-camera BEV transformers, and multimodal fusion models to extract and model lane and route networks for both high-fidelity offline pipelines and real-time online mapping.
- Architect, design, and implement a production-grade lane and route network mapping stack, ensuring high-performance integration with upstream and downstream modules like Perception, Behavior, Policy, and Prediction.
- Drive major feature development from inception to deployment. This includes high-level architecture design, rigorous code reviews, automated testing, mentorship of junior engineers, and technical resolution.
- Own the end-to-end data strategy for the mapping domain, specifically focusing on lane and route networks. You will define data curation, auto-labeling, synthetic data, and active learning pipelines to capture and resolve long-tail scenarios.
- Develop robust metrics and evaluation frameworks for lane and route network accuracy, temporal consistency, and scaling across diverse Operational Design Domains (ODDs).
- Work independently with cross-functional teams to translate complex autonomy goals into clear software and system requirements.
- Collaborate with ML and Autonomy engineers to ensure the seamless deployment and validation of mapping features to the vehicle fleet.
- Stay at the research frontier by evaluating, adapting, and innovating cutting-edge techniques, including online vectorized HD map construction, end-to-end mapping models, and vision/fusion Foundation Models to deliver production-ready solutions.
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 mapping or computer vision at scale.
- Deep expertise in several of the following areas:
- Vectorized mapping networks (e.g., MapTR), BEV-based scene representation, and temporal modeling.
- Cross-modal calibration and fusion (e.g., Camera-to-LiDAR) within Bird’s-Eye-View (BEV) unified representation spaces.
- Transformers or Graph Neural Networks (GNNs) applied to structured lane geometry and topological connectivity.
- Lane-level topology and connectivity, intersection modeling, and lane/road network graph construction.
- Computer Vision Foundations: Object detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction.
- Strong understanding of HD maps, including lane and road network geometry modeling, connectivity, and semantic attributes.
- Expertise in ML/DL development using PyTorch or TensorFlow, including experience with distributed training, synthetic data generation, large-scale dataset handling, and data curation strategies.
- Strong programming skills in Python and/or C++ with experience in modular software design and Linux-based development.
- Proven leadership in guiding technical roadmaps, mentoring engineers, and driving measurable improvements in model performance and system reliability.
- Strong communication skills with the ability to lead technical discussions and align with cross-functional teams.
- 10+ years of experience in ML/DL for autonomous driving or ADAS systems (desirable).
- Experience with self-supervised and/or semi-supervised learning for large-scale representation learning (desirable).
- Experience utilizing Vision-Language Models (VLMs) and/or Foundation Models for auto-labeling and long-tail (edge-case) detection (desirable).
- Expertise in ML optimization for real-time products with limited compute (desirable).
- A proven record of inventions and/or publication record at top-tier conferences (desirable).
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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