About the job
A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. As a Technical Program Manager with exceptional problem-solving skills, you will lead complex projects that explore the profound impact of data on the quality of our AI models and products. These projects span various stages, including training, testing, evaluation, and adaptation.
Responsibilities
Drive program outcomes for a portfolio of programs, focusing on efficiency, quality, and scalability.
Design, launch, standardize, and continuously optimize operational processes for various workflows.
Develop and implement frameworks for tracking and reporting on the delivery and quality of work, ensuring goals are met.
Act as the first point of contact for volume management and deliverable tracking, coordinating across multiple product areas.
Utilize data analysis to monitor performance, identify trends, and drive operational improvements.
Qualifications
Minimum
Bachelor's degree in a technical field, or equivalent practical experience.
8 years of experience in program management.
Experience working with data structures or machine learning algorithms.
Preferred
8 years of experience managing cross-functional or cross-team projects.
Experience working at companies specializing in data labeling and human-in-the-loop services.
Experience with SQL and data visualization tools.
Familiarity with AI/ML development lifecycles and the role of human-annotated data.
Knowledge of the data labeling industry, including best practices, challenges, and quality assurance techniques.