Program Manager, AI/ML

About the Program Manager, AI/ML Role at Google

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, AI/ML 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.

Minimum Qualifications

• Bachelor's degree in Computer Science, related technical field or equivalent practical experience.
• 5 years of experience managing dynamic programs, with engaging resource requirements and priorities.
• Experience in AI, machine learning, or related technologies.

Preferred Qualifications

• Ability to define projects and execute within timelines and with multiple stakeholders, and deliver projects on time and to budget.
• Ability to influence and communicate cross-functionally with all levels of management and having excellent communication skills.
• Ability to operate with high energy and flexibility in a fast-paced, constantly evolving work environment.
• Excellent project manager and takes initiative, with the ability to work independently and on multiple initiatives at the same time.

Responsibilities

• Direct delivery of programs, defining operational processes, headcount planning, and budgeting to ensure high-velocity execution in fast-paced environments.
• Partner with engineering and product to scale Human-in-the-Loop (HITL) micro-tasks, optimizing imagery curation and moderation to train and improve ML models.
• Guide critical analysis to uncover operational gaps, implementing scalable, measurable solutions that directly impact ML project success.
• Align globally dispersed teams and executive sponsors on progress and risk mitigation, resolving site-related differences to ensure seamless collaboration.
• Establish frameworks to measure AI improvements and lead high-priority pilots from concept to launch, scaling new data-acquisition methods to meet critical deadlines.

Key skills/competency

• Program Management
• Artificial Intelligence
• Machine Learning
• Project Leadership
• Cross-functional Collaboration
• Operational Planning
• Risk Mitigation
• Stakeholder Management
• Budgeting
• Process Optimization