May Mobility
Lead ML Engineer - Lane & Route Network Mapping
$220K–$270K
USA - Remote · Remote · Full-time · Posted Apr 24, 2026
- Experience
- 7+ years required; 10+ years in autonomous driving or ADAS is desirable.
- Education
- Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
About the job
Leads development and deployment of production-grade machine-learning systems that map lane and route networks for autonomous vehicles.
What you'll do
- Architect, train, validate, and deploy neural networks and mapping systems for offline and real-time lane and route mapping.
- Own mapping-domain data strategy and evaluation frameworks, including curation, auto-labeling, synthetic data, and long-tail scenario coverage.
- Lead technical development through architecture, code reviews, testing, mentorship, and cross-functional coordination.
What they ask for
- Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
- 7+ years of industry experience developing and deploying ML/DL models for mapping or computer vision at scale.
- Expertise in relevant mapping, computer vision, fusion, or topology methods, and ML/DL development using PyTorch or TensorFlow.
- Strong Python and/or C++ programming skills; proven technical leadership and strong communication skills.
Nice to have
- 10+ years of experience in ML/DL for autonomous driving or ADAS systems.
- Experience with self-supervised or semi-supervised learning, Vision-Language Models or Foundation Models, or real-time ML optimization.
Pay
$220,000 — $270,000 USD (base salary)
Tools
MapTR, PyTorch, TensorFlow, Python, C++, Linux, Transformers, Graph Neural Networks (GNNs)
AI focus
Develops neural networks, multimodal fusion, and mapping models for lane and route network extraction, including online mapping, auto-labeling, and long-tail scenario detection.
Model-written summary · the original posting is authoritative