NVIDIA

Software Engineering Manager, AI Infrastructure Services

NVIDIA

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $200,000 - $322,000 per year

Job Level

SeniorLead

Tech Stack

CloudDockerKubernetesOpenStack

About the role

  • Develop automation running reliable AI infrastructure services at scale; both close to the bare metal and over VMaaS.
  • Develop one or more teams to ensure that our internal and external facing cloud services atop of our hardware for accelerated computing are running as reliably as needed.
  • Recruit and retain talent managing career development for your organization.
  • Accountable for deliverables of team(s) in scope.
  • Be accountable for cross team and cross company communications.
  • Participate in KPI-driven strategic planning.
  • Foster a collaborative environment.

Requirements

  • 7+ overall years of experience
  • BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.
  • 3+ years of management experience with prior hands-on experience as an individual contributor.
  • A proven track record of impactful project deliveries while managing Software Engineers focused on cloud infrastructure or cloud application services.
  • Experience with DevOps and/or SRE practices and/or Platform Engineering.
  • Systematic problem-solving approach, coupled with strong communications skills and a sense of ownership and drive.
  • Developing ML/AI infrastructure (way to stand out)
  • Developing bare metal as a service (BMaaS) associated systems (way to stand out)
  • Developing multi-cloud infrastructure services (way to stand out)
  • Teaching reliability (e.g. SRE) or more general cloud systems good practices to peers or to other companies (e.g. CRE) (way to stand out)
  • Running private or public cloud systems based on one or more of Kubernetes, OpenStack, NVIDIA BCM, Docker or Slurm (way to stand out)
  • No prior experience having worked in a team of any particular name or having worked in a ML/AI focused team are required but also a nice to have.