Our client is a global technology consultancy known for its emphasis on agile software development, lean thinking, and promoting social and economic justice through tech.

What client is looking for

• Expertise in GPU-based infrastructure for AI (H100, GB200, or similar), including scaling across clusters.
• Strong knowledge of orchestration frameworks: Kubernetes, Ray, Slurm.
• Experience with inference-serving frameworks (vLLM, NVIDIA Triton, DeepSpeed).
• Proficiency in infrastructure automation (Terraform, Helm, CI/CD pipelines).
• Experience building resilient, high-throughput, low-latency systems for AI inference.Strong background in observability and monitoring: Prometheus, Grafana, OpenTelemetry.
• Familiarity with security, compliance, and governance concerns in AI infrastructure (data sovereignty, air-gapped deployments, audit logging).
• Solid understanding of DevOps, cloud-native architectures, and Infrastructure as Code.
• Exposure to multi-cloud and hybrid deployments (AWS, GCP, Azure, sovereign/private cloud).
• Experience with benchmarking and cost/performance tuning for AI systems.
• Background in MLOps or collaboration with ML teams on large-scale AI production systems.

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