1 day ago
Warsaw, PolandStaff+
Responsibilities
- Drive the end-to-end reliability, scalability, and performance of large-scale Models and AI workloads on Vertex AI.
- Architect and operate secure fleet-management automation for monitoring and upgrading large Google Cloud Platform and Google Kubernetes Engine environments.
- Optimize low-latency, high-throughput AI serving infrastructure and the efficiency, observability, and availability of accelerator resources.
- Partner with development teams on system design, launch reviews, and capacity planning for data and control planes.
- Build self-healing software, eliminate toil, and drive architectural changes that improve deployment velocity and platform resilience.
Requirements
- Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
- Eight years of experience with data structures and algorithms.
- Five years of software-development experience in one or more programming languages.
- Three years of experience leading projects and designing, analyzing, and troubleshooting distributed systems.
- Experience with computing, distributed systems, storage, or networking is preferred.
- Preferred qualifications include debugging and code optimization, automation of routine tasks, large-scale distributed-systems expertise, and strong problem-solving and communication skills.
- Interest in learning and applying new technologies in the AI/ML space and understanding complex system interactions is preferred.
Benefits
- The posting references Google benefits but does not detail specific benefits.
Tech Stack
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About Google
Google builds consumer and enterprise software and services including Search, Android, YouTube, Chrome, Maps, Gmail, and Google Cloud. Its business model centers on digital advertising and paid cloud, software, and hardware offerings (e.g., Pixel and Nest) for consumers, developers, and organizations. Founded in 1998 and headquartered in Mountain View, California, Google operates globally as a subsidiary of Alphabet Inc.