Senior Staff AI Governance Engineer

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 5 years of experience with design and architecture; and testing/launching software products.
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures and algorithms.
• 8 years of experience in developing infrastructure or solutions within large, complex, and cross-functional engineering environments.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• 2 years of experience with technical innovation in data governance or related fields.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will be passionate about ensuring comprehensive, automated, and ML lineage to enable AI governance at Google scale. You will be responsible for democratizing high-quality AI/ML data assets and infrastructure to enable Google to rapidly and iteratively deliver safe and impactful product experiences powered by AI models. You will accelerate trusted ML by making governance decisions automatically and will build scalable and automated infrastructure to manage ML assets at Google from development to launch with full traceability and auditability, without compromising developer velocity.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $248,000-$349,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Work with partners from Google DeepMind and Product Areas (e.g., Ads, Search, YouTube, Cloud, etc.) to drive lineage coverage and governance tooling adoption. Influence partners and stakeholders within and across the organizations to build joint roadmaps and drive outcomes for AI governance: understanding all datasets used, approvals in scope, and integrity status of models being launched and served in compliance with relevant regulations.
• Build systems and mechanisms which ensure that all AI models that Google develops are trained on the right data subject contingencies.
• Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.
• Provide technical leadership on projects and manage project priorities, deadlines, and deliverables.
• Design, develop, test, deploy, maintain, and enhance large-scale software solutions.