Exp. Required: 6+ Year’s
Must Have Technical/Functional Skills
• Demonstrated experience training, fine-tuning, and deploying machine learning models.
• Demonstrated experience generating and managing camera and LiDAR sensor datasets for
perception or machine learning applications.
• Experience designing data collection pipelines and ground truth generation workflows.
• Demonstrated experience in data annotation and quality assurance for autonomous systems or
computer vision projects.
• Demonstrated ability to define annotation guidelines, identify labeling defects, and deliver measurable
improvements in dataset accuracy.
• Strong Python skills and experience automating data validation, model evaluation, and machine
learning workflows.
• Understanding of computer vision datasets, model metrics, experiment tracking, version control, and
deployment practices.
Roles & Responsibilities
• Build automation for sensor-data ingestion, curation, sampling, annotation preparation, validation, and
release.
• Train, fine-tune, evaluate, and support deployment of machine learning models for computer vision or
perception use cases.
• Design camera and LiDAR data collection and ground truth generation pipelines.
• Define annotation guidelines, acceptance criteria, and automated checks for label completeness,
consistency, and accuracy.
• Analyze labeling defects and model-error patterns, then implement corrective actions and measurable
quality improvements.
• Create reporting for dataset health, annotation quality, model performance, and workflow throughput.
• Collaborate with data engineering, annotation operations, quality, and AI teams.
Generic Managerial Skills, If Any
Strong technical ownership, analytical problem solving, collaborative delivery, and clear communication
with cross-functional teams
