Operations Manager, AI/ML Data Solutions

About the Job

In this role, you will join the Global Video Operations (GVO) Solutions Lab function where we are leading the transition to an AI-first model to drive process automation, improve accuracy, and deliver exceptional consumer, creator and partner experiences. You will work closely with the Business, Engineering, Product Management, Data Science, Trust and Safety and Risk and Compliance teams to deliver exceptional operations that power critical workflows and needs across YouTube.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $136000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Identify and evaluate opportunities for AI-powered workflows and advance our nextgen vendor capabilities.
• Manage end-to-end operations for Human-in/on-the-loop programs, including solution design and overall vendor strategy.
• Enable AI-readiness by ensuring labelled data is structured and compatible with downstream automation use cases.
• Partner closely with Tech and Business (Biz) teams to develop frameworks for collecting high quality labels for training and testing AI solutions for various use cases within the Creator, Consumer, Trust and Safety organizations.
• Develop and maintain the overall workflow strategy, identify and mitigate risk from a delivery standpoint and ensure compliance with all internal policies and procedures.

Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 7 years of experience in management consulting focused on strategy and operations.
• Experience developing AI-based operational solutions for organizations.
• Experience in vendor operations management or overseeing vendor operations programs.

Preferred qualifications:

• Experience as a Technical Program Manager/Program Manager for an outsourced operations within Engineering organizations.
• Experience building and reporting on meaningful business metrics, with excellent data analysis and influencing skills.
• Understanding of ML training of perception models and associated inputs (e.g., calibration), data infrastructure, and visualization tooling.
• Proven track record of working with Business and Product/Engineering teams in a changing environment.