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Duration: 920 Hours
Location: Charlotte, NC or Jersey City, NJ (3 days a week onsite) -- Resource will choose which site
HYBRID Schedule
Must have skills: LLM and Kubernetes
Project Tasks:
AI Operations Platform Consultant
Experience deploying, managing, operating, and troubleshooting containerized services at scale on Kubernetes for mission-critical applications (OpenShift)
Experience with deploying, configuring, and tuning LLMs using TensorRT-LLM and Triton Inference server.
Managing MLOps/LLMOps pipelines, using TensorRT-LLM and Triton Inference server to deploy inference services in production
Setup and operation of AI inference service monitoring for performance and availability.
Experience deploying and troubleshooting LLM models on a containerized platform, monitoring, load balancing, etc.
Operation and support of MLOps/LLMOps pipelines, using TensorRT-LLM and Triton Inference server to deploy inference services in production
Experience deploying and troubleshooting LLM models on a containerized platform, monitoring, load balancing, etc.
Experience with standard processes for operation of a mission critical system incident management, change management, event management, etc.
Managing scalable infrastructure for deploying and managing LLMs
Deploying models in production environments, including containerization, microservices, and API design
Triton Inference Server, including its architecture, configuration, and deployment.
Model Optimization techniques using Triton with TRTLLM
Model optimization techniques, including pruning, quantization, and knowledge distillation
Duration: 920 Hours
Location: Charlotte, NC or Jersey City, NJ (3 days a week onsite) -- Resource will choose which site
HYBRID Schedule
Must have skills: LLM and Kubernetes
Project Tasks:
AI Operations Platform Consultant
Experience deploying, managing, operating, and troubleshooting containerized services at scale on Kubernetes for mission-critical applications (OpenShift)
Experience with deploying, configuring, and tuning LLMs using TensorRT-LLM and Triton Inference server.
Managing MLOps/LLMOps pipelines, using TensorRT-LLM and Triton Inference server to deploy inference services in production
Setup and operation of AI inference service monitoring for performance and availability.
Experience deploying and troubleshooting LLM models on a containerized platform, monitoring, load balancing, etc.
Operation and support of MLOps/LLMOps pipelines, using TensorRT-LLM and Triton Inference server to deploy inference services in production
Experience deploying and troubleshooting LLM models on a containerized platform, monitoring, load balancing, etc.
Experience with standard processes for operation of a mission critical system incident management, change management, event management, etc.
Managing scalable infrastructure for deploying and managing LLMs
Deploying models in production environments, including containerization, microservices, and API design
Triton Inference Server, including its architecture, configuration, and deployment.
Model Optimization techniques using Triton with TRTLLM
Model optimization techniques, including pruning, quantization, and knowledge distillation
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