Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience testing, and launching software products.
  • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  • 5 years of experience with distributed systems, data analytics, and applied ML.
  • Experience with ML algorithms (e.g., LLMs, Stable Diffusion or Ranking and Recommendation).

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures/algorithms.
  • 3 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.
  • Knowledge in Kubernetes.

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.

Kubernetes (K8S) is a portable, extensible open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes builds upon a decade and a half of experience that Google has with running production workloads at scale, combined with best-of-breed ideas and practices from the community. Google Kubernetes Engine (GKE) is a hosted version of Kubernetes running on Google Cloud Platform providing an extra layer of automation and zero devops to allow for frictionless use of K8S.

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 $197,000-$291,000 + 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

  • Provide technical leadership on high-impact projects, driving innovation on GKE AI/ML workload efficiency and optimization.
  • Influence, coach and mentor a distributed team of engineers helping to to shape the culture of the team to be a high executing, fun team.
  • Facilitate alignment and clarity across teams on goals, outcomes, and timelines while managing project priorities, deadlines, and deliverables.
  • Design, develop, test, deploy, maintain, and enhance large scale software solutions.
  • Identify gaps and drive improvement across entire GKE/GCE stack.
Read Full Description
Confirmed 4 hours ago. Posted 5 days ago.

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