Senior Data Scientist, Data Quality and AI Evaluation

Description

The company is building an AI-native architecture for autonomous driving that combines classical safety stacks, foundation models and scalable AI systems into one production platform.

The future of autonomous vehicles lies in tightly joining proven safety architectures with large-scale AI, rather than relying only on classical robotics or only on end-to-end neural networks.

The team works on problems that will shape autonomous systems over the coming decade.

Responsibilities

• Set quality measures and evaluation methods that show where auto-labeling pipelines perform well, break down, or get worse.
• Create and maintain human-verified golden datasets that cover typical driving conditions, hard edge cases, past failures and newly added requirements.
• Examine large volumes of sensor, camera and annotation data to find root causes and systematic errors, then rank fixes with perception and auto-labeling engineers.
• Build automated methods for grouping failures, finding similar cases and selecting the right data for human correction.
• Design statistically sound audits and experiments, define release acceptance criteria, and share findings through clear dashboards and recommendations.
• Work with labeling operations to refine annotation guidelines and reviewer consistency, balancing quality, speed and cost.

Requirements

• Strong grounding in statistics, experimental design, sampling, hypothesis testing and uncertainty estimation, with hands-on experience evaluating machine learning systems and data quality.
• Experience evaluating AI or LLM systems, with proficiency in Python and SQL, analyzing large datasets and building reproducible analysis workflows.
• Working knowledge of precision, recall, class imbalance, selection bias, data leakage and evaluation across significant scenario groups.
• Ability to tell reference-label defects apart from model errors, and to turn vague quality concerns into measurable questions and practical recommendations.
• Strong communication and teamwork skills, with experience working across engineering, research, product or operations teams.
• 12+ years of industry experience and a Bachelor's degree in statistics, mathematics, computer science, engineering or a related quantitative field. A Master's degree with a proven track record, or equivalent practical experience, is also accepted.

Conditions

Applications are accepted at least until November 3, 2026.

This is an existing vacancy.

The company uses AI tools in its recruiting process.

Base salary depends on location, experience and other objective job-related factors. The expected base salary range is 224,000 USD to 356,500 USD for Level 5, and 272,000 USD to 431,250 USD for Level 6.

The company is an equal opportunity employer and does not discriminate on the basis of any protected characteristic.