Software Engineer, Ml Fleet Intelligence

Google

Sunnyvale, CA, United States
Base: $207,000-$300,000; bonus/equity: included; b...
Not specified (assumed to be hybrid or onsite based on company culture)
Ai/ml model design and implementation
Petabytes of telemetry data analysis
Scalable automated system development
Google is seeking a Software Engineer for its ML Fleet Intelligence team in Sunnyvale, CA, to develop innovative AI/ML solutions that enhance the reliability of its data center infrastructure. The ideal candidate will possess a versatile skill set in software engineering and machine learning, with experience in large-scale system design and a passion for tackling complex challenges

Job Summary

  • This role involves taking control of the world's largest data center footprint as an Applied AI/ML Specialist responsible for the fault tolerance of Google's entire fleet.
  • Engineers will pioneer the use of AI/ML to solve complex infrastructure challenges by leveraging petabytes of operational and telemetry data.
  • The position offers opportunities to switch teams and projects while working on critical initiatives that drive Google's future innovations.

Matching Summary

Match Score: 85

Google is seeking a Software Engineer for its ML Fleet Intelligence team in Sunnyvale, CA, to develop innovative AI/ML solutions that enhance the reliability of its data center infrastructure. The ideal candidate will possess a versatile skill set in software engineering and machine learning, with experience in large-scale system design and a passion for tackling complex challenges.

Salary

Base: $207,000-$300,000; Bonus/Equity: Included; Benefits: Not specified

Skills & Requirements

Must-have

  • AI/ML model design and implementation
  • Petabytes of telemetry data analysis
  • Scalable automated system development
  • Hardware and software fault mitigation
  • Data center infrastructure reliability

Nice-to-have

  • Leadership qualities in fast-paced environments
  • Versatility across full-stack technologies
  • Experience with distributed computing systems
  • Collaboration with hardware designers
  • Innovation in large-scale system design

Key Requirements

  • Specialized ML area expertise
  • Experience with ML TPUs
  • Background in distributed computing
  • Skills in large-scale system design

Work Rights

Not specified

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