Gary Innerarity 👋

Platform Architect • Digital Twins • AI Orchestration

I build platforms that turn infrastructure, data, and AI models into working systems.

My work focuses on designing orchestration layers that connect:

• Cloud infrastructure
• AI and ML workloads
• Real-time data
• Edge devices
• Operational dashboards

Most projects revolve around building reusable platforms instead of one-off solutions.

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🔭 Current Focus

AI & ML Orchestration Platforms

Designing orchestration systems for:

• LLM inference workloads
• ML pipelines
• Multi-model serving
• GPU resource scheduling
• Scalable API endpoints
• Distributed inference

Technologies:

• Kubernetes
• Ray
• vLLM
• Terraform
• Docker
• Python

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Digital Twin Platforms

Building real-time digital twin environments combining:

• Telemetry ingestion
• Cloud infrastructure
• Edge devices
• Simulation pipelines
• Interactive dashboards

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Automation Platforms

Designing workflow-driven operational systems:

• API integrations
• Dashboard-driven operations
• Event-based automation
• System monitoring

Technologies:

• Node-RED
• FlowFuse
• REST APIs
• Data pipelines

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🧠 Core Platform Skills

Infrastructure Platforms

• Kubernetes platform design
• Infrastructure-as-Code (Terraform)
• Container orchestration
• Cloud networking
• Observability pipelines

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AI Infrastructure

• LLM inference infrastructure
• GPU orchestration
• Model serving platforms
• Distributed compute
• High-throughput APIs

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Development

• Python
• Javascript
• API design
• Automation frameworks
• Data processing

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Edge Systems

• Raspberry Pi clusters
• Sensors & tracking
• Robotics experiments
• Edge → Cloud pipelines

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🚧 Notable Projects

GenAI / ML Orchestration Platform

Platform for managing AI workloads across distributed infrastructure.

Capabilities:

• Multi-model inference
• GPU scheduling
• Kubernetes-native deployments
• API-driven model access
• Scalable inference endpoints
• Ray-based distributed workloads

Typical stack:

• Kubernetes
• Ray
• vLLM
• Terraform
• Python

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Digital Twin Infrastructure

Real-time modeling of physical environments.

Capabilities:

• Telemetry ingestion
• Simulation pipelines
• Infrastructure modeling
• Visualization dashboards
• Edge device integration

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Automation Control Platforms

Operational automation platforms designed for real-world workflows.

Capabilities:

• Workflow orchestration
• System integrations
• Data-driven dashboards
• API automation
• Monitoring pipelines

Technologies:

• Node-RED
• FlowFuse
• Cloud APIs

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🛠 Technology Stack

Core

Cloud

Edge

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📫 Contact

LinkedIn: https://www.linkedin.com/in/garyinnerarity/

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⚡ Engineering Philosophy

• Build platforms, not scripts
• Automate everything repeatable
• Design for scale first
• Observe everything
• Ship working systems
• Engineer for failure