Related skills
docker prometheus python kubernetes nvidia triton📋 Description
- Deploy and optimize model-serving platforms (Triton/vLLM/KServe) in Rackspace Private Cloud/Hybrid.
- Bridge AI engineering and platform ops for secure, scalable inference services.
- Deploy models in Kubernetes; tune latency and throughput to meet SLAs.
- Integrate models with Rackspace Unified Inference API and API Gateway for multi-tenant routing.
- Enable Observability and FinOps for GPU utilization and cost reporting.
- Support customers and onboarding for BFSI/Healthcare and other verticals.
🎯 Requirements
- Hands-on with NVIDIA Triton, vLLM, or similar serving stacks.
- Strong Kubernetes, GPU scheduling, and CUDA/MIG knowledge.
- Familiarity with VMware VCF9, NSX-T, and vSAN.
- Proficiency in Python and Docker.
- Observability stacks (Prometheus, Grafana) and FinOps.
- Customer-facing communication skills.
🎁 Benefits
- NVIDIA Certified Professional (AI/ML) preferred.
- Kubernetes Administrator (CKA) preferred.
- VMware VCF Specialist preferred.
- Rackspace AI Foundations (internal) preferred.
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