Job description

In this role, you will build infrastructure that powers many Vertex AI products and solutions, including Gen AI, Agent, Document AI, Vision AI etc. Also, you will build foundational infrastructure to make Vertex AI more enterprise ready by providing advanced security and compliance features (e.g., access control, auth, security horizontals). The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . • Write product or system development code. • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. • Design and implement changes to make Cloud AI products more enterprise-ready (customer managed encryption key, access transparency, etc) in order to unblock customers in certain industries (e.g., financial industry, healthcare) • Lead, design, review and implement business critical infra for Vertex AI products. • Build Vertex AI into the full lifecycle of customer's machine learning workflows by improving interoperability within multiple Vertex AI products and with other GCP/non-GCP services. • Bachelor’s degree or equivalent practical experience. • 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting. • 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture. • Experience building software for data privacy or security. • Experience in AI/ML related engineering, developing, deploying, managing, and maintaining Machine Learning infrastructure. Minimum qualifications: • Bachelor’s degree or equivalent practical experience. • 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting. • 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture. • Experience building software for data privacy or security. • Experience in AI/ML related engineering, developing, deploying, managing, and maintaining Machine Learning infrastructure. Preferred qualifications: • Master's degree or PhD in Computer Science or related technical fields. • 2 years of experience with data structures and algorithms. • Experience developing accessible technologies.

Requirements

Must-haves

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Write product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Lead, design, review and implement business critical infra for Vertex AI products.
Build Vertex AI into the full lifecycle of customer's machine learning workflows by improving interoperability within multiple Vertex AI products and with other GCP/non-GCP services.
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
Experience building software for data privacy or security.
Experience in AI/ML related engineering, developing, deploying, managing, and maintaining Machine Learning infrastructure.
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
Experience building software for data privacy or security.
Experience in AI/ML related engineering, developing, deploying, managing, and maintaining Machine Learning infrastructure.
2 years of experience with data structures and algorithms.

Nice-to-haves

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Master's degree or PhD in Computer Science or related technical fields.
Experience developing accessible technologies.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learninggcpml

Platform: google
Effort: medium

Benefits

Benefits detected in the listing.

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