Senior Data Quality Engineer, Data Quality Services
Core
Define, measure, and automate quality for training and validation data used for robotics, autonomy, computer vision, and Vision-Language-Action (VLA) systems.
Role type
Senior IC data quality engineer (multimodal sensor data)
Builds
Automated quality gates, metrics, and validation tooling for datasets from raw camera and LiDAR captures to auto-labeled annotations and captions
Domain
Autonomous construction sites, physical AI, computer vision, multimodal AI
Deliverable
production ML models
Required skills
Python, SQL, data pipeline design, data validation frameworks, statistics and sampling, camera and LiDAR sensor data management, annotation guidelines definition, dataset management tools, machine learning frameworks
Preferred skills
computer vision, robotics, autonomy, Physical AI, AI-assisted quality techniques, vision-language model evaluation, data lineage and versioning, cloud platforms, MLOps, vendor quality program management
Technologies
NVIDIA Cosmos Curator, Cosmos Reason, Labelbox, CVAT, FiftyOne, PyTorch, MLflow, Docker, Kubernetes, DVC, Airflow
Responsibilities
Define data quality standards and annotation guidelines for sensor data and labels; Build automated quality gates validating data from ingestion through publication; Develop AI-driven quality checks like label-noise detection and caption verification; Define and track dataset quality KPIs and share results via dashboards; Audit internal and vendor annotations using gold datasets and manage annotation providers; Analyze dataset coverage and gaps to trace model failures back to data issues
Seniority
Senior, hands-on IC
