| On-prem Platform Engineer | | Brevard, Charlotte | Arize AI, Claude Cowork, Google Cloud Platform, Terraform | vLLM TensorRT LLM Triton Inference Server SGLang Inference Optimization Continuous Batching Speculative Decoding KV Cache / Prefix Caching FP8 / AWQ / GPTQ Tensor Parallelism Kubernetes ML Serving KServe OpenShift AI Helm / Operators GPU Orchestration Run:AI Performance Benchmarking CUDA / NCCL / MIG Prometheus / Grafana ML Observability GuideLLM, Locust | Build, configure, and operate on prem Kubernetes/OpenShift AI platforms for deploying and serving GenAI models and LLM inference workloads. Design and optimize high performance inference stacks using vLLM, TensorRT LLM, Triton Inference Server, SGLang, and advanced techniques (continuous batching, speculative decoding, KV caching). Manage GPU orchestration and capacity using Run:AI, MIG, CUDA/NCCL, and tensor parallelism to maximize utilization and throughput. Deploy and operate Kubernetes ML serving frameworks (KServe, Helm, Operators) for scalable, reliable model serving. Drive inference optimization and benchmarking, leveraging FP8, AWQ, GPTQ, and performance tools such as GuideLLM and Locust. Implement observability and ML monitoring using Prometheus, Grafana, Arize AI, ensuring SLA/SLO compliance for GenAI services. Collaborate with ML and research teams to onboard new models, tune inference performance, and productionize GenAI use cases. |
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