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Hpc Operations Engineering Manager

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Microsoft Corporation

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Location:
United States , Mountain View

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

139900.00 - 274800.00 USD / Year
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Job Description:

Microsoft AI is seeking an experienced HPC Operations Engineering Manager to join our Infrastructure Team. In this role, you’ll lead a team of Site Reliability Engineers who blend software engineering and systems engineering to keep our large-scale distributed AI infrastructure reliable and efficient. You’ll work closely with ML researchers, data engineers, and product developers to design and operate the platforms that power training, fine-tuning, and serving generative AI models.

Job Responsibility:

  • Team leadership: Lead a team of experienced SREs to ensure uptime, resiliency and fault tolerance of AI model training and inference systems
  • Observability: Design and help maintain monitoring, alerting, and logging systems to provide real-time visibility into model serving pipelines and infra
  • Automation & Tooling: Lead building of automation for deployments, incident response, scaling, and failover in hybrid cloud/on-prem CPU+GPU environments
  • Incident Management: Lead on-call rotations, troubleshoot production issues, conduct blameless postmortems, and drive continuous improvements
  • Security & Compliance: Ensure data privacy, compliance, and secure operations across model training and serving environments
  • Collaboration: Partner with ML engineers and platform teams to improve developer experience and accelerate research-to-production workflows

Requirements:

  • Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with Site Reliability Engineering, DevOps, or Infrastructure Engineering Leadership roles AND 8+ years experience with Kubernetes, Docker, and container orchestration, AND 8+ years experience with public cloud platforms like Azure/AWS/GCP and infrastructure-as-code, AND 6+ years experience with programming/scripting skills not limited to Python, Go, or Bash
  • OR equivalent experience
  • Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience AND 10+ years experience with Kubernetes, Docker, and container orchestration, AND 10+ years' experience with public cloud platforms like Azure/AWS/GCP and infrastructure-as-code
  • OR equivalent experience
  • 6+ years people management experience
  • Experience in monitoring & observability tools (Grafana, Datadog, OpenTelemetry, etc.)
  • Experience running large-scale GPU clusters for ML/AI workloads
  • Experience with high-performance computing (HPC) and workload schedulers (Kubernetes operators)
  • Knowledge of CI/CD pipelines for Inference and ML model deployment
  • Solid knowledge of distributed systems, networking, and storage
  • Familiarity with ML training/inference pipelines
  • Background in capacity planning & cost optimization for GPU-heavy environments

Additional Information:

Job Posted:
February 16, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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