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Engineering Manager, Nexus ML, Google Global Fleet

Google
Posted 10 hours ago, valid for a month
Location

Seattle, WA, US

Salary

$207,000 - $300,000 per year

Contract type

Full Time

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Sonic Summary

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  • The job requires a Bachelor's degree in Computer Science or a related field, along with 8 years of software development experience and 3 years managing a technical team.
  • Candidates should have experience in architecting and developing distributed systems and familiarity with large-scale infrastructure, data pipelines, or analytics.
  • The role involves managing a team of software engineers and leading the design and development of large-scale distributed systems.
  • The salary for this position ranges from $207,000 to $300,000, with additional benefits including a 20% bonus target and equity.
  • This position is part of the AI and Infrastructure team at Google, focusing on delivering innovative capabilities and insights at scale.

Minimum qualifications:

  • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  • 8 years of experience in software development.
  • 3 years of experience managing a technical team.
  • Experience with software development using a general-purpose programming language.
  • Experience architecting and developing distributed systems.

Preferred qualifications:

  • Experience with large-scale infrastructure and distributed systems.
  • Experience with data pipelines, analytics, or billing systems.

About the job:

Google owns and operates data centers all over the world, helping to keep the internet humming 24/7. Keeping our data centers running and further growing our data center fleet requires software that operates at Google scale.

We are a Seattle/Kirkland based engineering team with a broad portfolio of products and technologies. We take pride in our unique highly collaborative style of development and are responsible for Demand Visibility and highly optimized supply chain execution across Alphabet.

As a part of efficient and optimal supply chain operations we are building a demand tracking platform that enables our customer to always stay on top of their order health and provides execution teams a standard conduit to expose risks and exceptions. Up until recently, much of that was a manual process, but our business is growing geometrically and humans with spreadsheets don't scale. Our team is dedicated to bringing intelligence to both the tactical and strategic needs for visibility, specifically for machine and network components. We operate like a small business, and our customers are everyone from the product area planners to the folks on the ground in Supply Chain Operations working to deliver machines, transport assets, forecast or just counting capitalized dollars of things landed.

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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

  • Manage and grow a team of software engineers, fostering a culture and guiding their career development.
  • Lead the design, development, and architecture of large-scale distributed systems and data pipelines.
  • Drive the technical strategy and roadmap for Nexus machine learning (ML) capacity engineering initiatives.
  • Collaborate with cross-functional stakeholders to integrate multi-component systems and ensure their successful adoption.
  • Guide software development best practices using general-purpose programming languages to deliver scalable, high-quality infrastructure solutions.


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