Autonomous Vehicle Data Quality Engineer

Hardware FYI; Sunnyvale, Northern (CA, KY); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Applied Intuition, Inc. is seeking a Data Quality Specialist to safeguard the integrity of autonomous vehicle data across test drives and lab datasets. You will implement automation to verify data, identify anomalies, and support labeling for model training in a fast-paced AV environment.

Ideal candidates bring 2+ years in data analysis or QA, experience with sensor data, and strong attention to detail. Collaboration with engineering and data teams is essential.

Qualifications

• 2+ years experience in data analysis, quality assurance, or related technical field.
• Familiarity with data annotation tools and workflows.
• Experience with data validation techniques and quality control processes for AV domain.
• Attention to detail and analytical mindset.
• Experience with sensor data (LiDAR, radar, camera) from autonomous vehicles.
• Strong problem-solving abilities and communication skills.

Responsibilities

• Review and validate data collected from test drives to ensure completeness, accuracy, and relevance.
• Develop and implement automation scripts to streamline data verification processes.
• Identify anomalies, inconsistencies, and quality issues in collected datasets.
• Assist with data annotation and labeling to support machine learning model training.
• Document quality standards and create comprehensive reports on data quality metrics.
• Collaborate with engineering teams to improve data collection methodologies.
• Support the continuous improvement of data verification workflows.

Skills

Data analysis

Quality assurance

Attention to detail

Analytical mindset

Communication skills

Problem-solving

Tools

Python

Linux

Jira

Confluence

Data labeling tools

Automation scripting

Job description

Applied Intuition, Inc. is seeking a Data Quality Specialist to safeguard the integrity of autonomous vehicle data across test drives and lab datasets. You will implement automation to verify data, identify anomalies, and support labeling for model training in a fast-paced AV environment.

Ideal candidates bring 2+ years in data analysis or QA, experience with sensor data, and strong attention to detail. Collaboration with engineering and data teams is essential.