The opportunity
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to…
What you'll do
Own End-to-End Dataset Creation: Take full ownership of the ML dataset lifecycle, including supporting demand planning, owning capacity plans, managing policy creations, overseeing execution, and implementing quality management processes.
Lead Strategic Planning/Resource Allocation and quality management: Lead and manage monthly, quarterly, and annual capacity planning cycles to ensure resources are strategically allocated and aligned precisely with product demand. The candidate will also take direct ownership of the quality of the delivered datasets.
Manage Stakeholder Collaboration: Collaborate closely with engineering partners and label requestors to fulfill dataset requirements on time and within budget,
Establish Robust Governance: Set up governance structures and review mechanisms to monitor, measure, and effectively communicate program/project progress to stakeholders, executives, and sponsors.
Drive Continuous Improvement at Scale: Partner with cross-functional teams (Engineering, Infra, Product) locally and globally to drive continuous vertical and horizontal operational improvements.
Manage Vendor Operations and Problem Solving: Work with vendor partners to manage scaled operations, revise the organizational structure, and proactively solve current and future issues in the labeling process using a data-driven approach.
What they're looking for
- A Bachelor's Degree in technical or business discipline with overall 8+ years: of work experience managing large-scale and dynamic programs/ projects
- Extensive experience managing Product Operations or successfully executing: multiple cycles of product execution programs.
- Background in leading and managing complex programs that span across: organizations and functions, with specific experience in Machine Learning data annotation or Human-in-the-Loop initiatives.
- Proven proficiency in defining projects, executing them within timelines, and: the ability to work independently on multiple complex initiatives concurrently.
