Group Product Manager, AI Data Quality

Google is seeking a Group Product Manager for AI Data Quality to lead their data quality initiatives across AI applications, with a particular focus on Gemini. This role combines technical expertise in data science and AI/ML with strategic product management to ensure the highest quality data for AI model training. The position offers a competitive compensation package of $214,000-$305,000 plus bonus, equity, and benefits.

As the Group Product Manager, you'll be at the forefront of shaping AI's future by defining and implementing products that ensure optimal data quality for model training. The role requires a deep understanding of data quality concepts, cloud platforms, and various data types, including both structured and unstructured formats. You'll work closely with engineering, research, and design teams to develop innovative solutions for data quality challenges at scale.

The ideal candidate brings 10 years of product management experience, preferably with a focus on data-driven products or AI/ML. A bachelor's degree in Computer Science or related field is required, with a master's degree being preferred. Your experience should encompass data science, analytics, and cloud platforms, with additional knowledge in ad quality and search quality being valuable assets.

Working at Google means joining a team that puts users first and adapts continuously to change. You'll be part of Google Cloud, which serves customers in over 200 countries, helping organizations digitally transform their businesses. The role offers the opportunity to impact millions of users while working with cutting-edge technology and world-class professionals.

This position combines strategic thinking with hands-on product development, requiring someone who can break down complex problems and drive solutions from conception to launch. You'll be responsible for conducting market research, analyzing competition, and translating business requirements into product specifications. The role offers the chance to work on groundbreaking AI technologies while ensuring they're built on a foundation of high-quality data.