Machine Learning Infrastructure Engineer
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with Machine Learning Infrastructure.
- 2 years of experience with data processing.
- 2 years of experience with coding in C++, Python, or 1 year of experience with an advanced degree.
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 2 years of experience with data lineage.
- 2 years of experience with graph algorithms.
- 2 years of experience with graph mining.
About the job
As a part of the AI Data organization, you will play key role in democratizing high-quality AI/ML data assets and infrastructure to enable the rapid and iterative delivery of safe, innovative, and impactful product experiences powered by AI models. As a member of the AI Governance and Lineage team, you will contribute to accelerating trusted ML by automating governance decisions and building scalable infrastructure that manages ML assets from development to launch, ensuring full traceability and auditability, without compromising development velocity across AI Governance, AI Lineage, AI asset security, AI asset approval management, and compliance verification and enforcement for GDM, product teams in product areas, and third-party clients of Cloud.The US base salary range for this full-time position is $147,000-$211,000 + 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
- Establish an authoritative source of truth by designing and building a comprehensive inventory of all AI assets, such as models and datasets, across Alphabet to serve as the foundational source of truth for where these assets exist in storage systems.
- Develop solutions to process a vast lineage graph of billions or trillions of nodes and edges and reduce it into a consistent inventory of AI assets and their relationships to one another.
- Build infrastructure that supports critical processes responsible for governing the security and launch of AI models at Alphabet.
- Work from high level ML tooling and frameworks.
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