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Locurile de muncă ale companiei

Senior Platform Software Engineer, AI/ML GPU Infrastructure

Build Cisco’s AI compute platform and GPU infrastructure, including Kubernetes control planes, GPU scheduling, and distributed systems at scale.

USStatele Unite ale AmericiiCACaliforniaNCCarolina de Nord
167.700 $ – 245.200 $ / an
HibridNormă întreagăSeniorLimbă Obligatorie: englezăInginer AIInginer de învățare automată
CloudGoKubernetesLinuxNode.jsOpenShiftPythonSisteme distribuite

Descriere

  • Build control-plane services, APIs, and controllers for multi-cluster operations, tenant onboarding, and GPU quota enforcement.
  • Set the technical architecture for GPU capacity scheduling and allocation, including fractional GPUs, tenant isolation, and workload-aware scheduling.
  • Create automated tools for capacity intake, demand classification, and request routing.
  • Develop automated recovery tools for node and workload failures.
  • Improve system-wide performance for training and inference workloads.
  • Build and scale Kubernetes platforms with OpenShift or upstream Kubernetes.
  • Lead design reviews and establish standards for platform services, Kubernetes Operators, Controllers, CRDs, and Go or Python automation.
  • Mentor engineers and strengthen cloud-native engineering and platform reliability practices.
  • Advance Infrastructure as Code, GitOps, and CI/CD automation.
  • Take part in on-call rotations, incident response, and postmortem reviews.

Cerințe

  • Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical experience
  • At least 8 years of software engineering experience building, architecting, or extending Kubernetes platforms or large-scale distributed systems
  • Experience providing technical leadership
  • Strong proficiency in Go or Python
  • Experience designing platform control-plane services, custom APIs, Kubernetes Controllers, Operators, or CRDs
  • Hands-on experience with batch and accelerator schedulers such as Kueue, Volcano, Slurm, or custom scheduler plugins for GPU or AI/ML workloads
  • Deep experience with GPU scheduling, multi-tenant GPU infrastructure, or accelerated compute platforms
  • Experience with Infrastructure as Code, GitOps, CI/CD, and cloud-native observability tools
  • Preferred: experience scaling Kubernetes control-plane internals or multi-cluster federation
  • Preferred: familiarity with NVIDIA H100, H200, B200/B300, AMD Instinct, NVLink, and InfiniBand
  • Preferred: familiarity with topology-aware placement, NCCL, and gang scheduling
  • Preferred: experience supporting AI/ML infrastructure, model serving, distributed training, workload orchestration, or MLOps
  • Preferred: experience tuning the Linux kernel or working with cgroups or eBPF
  • Preferred: experience leading ambiguous platform initiatives from start to finish
  • Preferred: experience with on-call rotations, incident response, and postmortem or runbook processes

Beneficii

  • Medical, dental, and vision insurance
  • 401(k) plan with Cisco matching contributions
  • Paid parental leave
  • Short- and long-term disability coverage
  • Basic life insurance
  • Eligibility for Cisco restricted stock unit grants
  • 10 paid holidays per full calendar year
  • One floating holiday for non-exempt employees
  • Paid day off for your birthday
  • Paid year-end holiday shutdown
  • Four paid personal wellness days
  • 16 days of paid vacation per full calendar year for non-exempt employees
  • Flexible vacation time off program for exempt employees
  • 80 hours of sick time provided at hire and each January 1, with up to 80 unused hours carried forward
  • Additional paid time away for critical or emergency family issues
  • Optional 10 paid volunteer days per full calendar year
  • Annual bonuses for non-sales roles, subject to Cisco policies

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