Quality Lead, YouTube Global Vendor Operations
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 7 years of experience with QA automation and sampling tools.
- 7 years of experience in Large Language Model (LLM) evaluation.
- Experience with LLM-based evaluation frameworks and prompt engineering.
- Experience in contact center metrics and QA methodologies.
Preferred qualifications:
- MBA or Master's degree in a related field or Council of Supply Chain Management Professionals (CSCMP) certification.
- 7 years of experience using data analysis to drive decision making.
- 7 years of experience building relationships with stakeholders or clients.
- Experience in data center equipment environments or computer component manufacturing.
- Excellent problem-solving skills with the ability to apply structured thinking and logic to your work and provide solutions to challenges.
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 Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.
The YouTube Global Vendor Ops (GVO) team develops practical and innovative ways to address some of the most complex business challenges to keep YouTube thriving. We anticipate how decisions are made, persistently explore and uncover the business needs of our key clients, and understand how our range of product and service offerings can enable their business success. We lead the global vendor quality program which enables our suppliers to deliver amazing experiences for YouTube’s consumers, creators and partners.
In this role, you will drive the transition to an automated quality assurance ecosystem. You will be a key player in scaling Artificial Intelligence (AI)-motivated evaluations to 100% of customer interactions while ensuring the highest levels of model accuracy and reliability.
Responsibilities
- Design Quality Assurance (QA) frameworks to ensure alignment with key business outcomes. Monitor AI QA model performance and accuracy using metrics such as precision, recall, and human interrater agreement.
- Manage the ingestion of human-validated golden labeling from manual overrides to drive continuous, high-fidelity model retraining.
- Implement blind review protocols and complex multi-tiered human+AI arbitration to prevent automation bias.
- Design stratified sampling methodologies that prioritize high-risk or ambiguous interactions (e.g., cases where AI confidence is low) for human review.
- Partner with the training team to remediate quality gaps.
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