MLE, Data Enrichment
Core
Build ground-truth datasets and classifiers for complex driving scenes to support perception and driving models for autonomous driving systems.
Role type
Machine Learning Engineer (Data Enrichment)
Builds
Ground-truth datasets, classifiers, and reusable tools for annotation, training, and inference.
Domain
Autonomous driving, computer vision, data enrichment.
Deliverable
production ML models
Required skills
Computer vision model development and evaluation, Python programming, PyTorch, dataset curation, annotation quality assessment, error analysis, model failure investigation.
Preferred skills
3D geometry, multi-camera systems, temporal scene understanding, autonomous driving/ADAS/robotics, foundation/vision-language models, human annotation workflows, active learning, SQL, distributed data processing.
Responsibilities
Define scene attributes and dataset requirements, design annotation tasks and labelling instructions, curate ground-truth datasets, build and evaluate computer vision models, use error analysis to improve data and model performance.
Seniority
Mid-level, hands-on IC