Building AI Infrastructure, Distributed Inference Systems, and Workflow Orchestration Platforms.

AI Systems Engineer with experience architecting production AI systems, multimodal generation platforms, distributed GPU infrastructure, and workflow execution engines.

Architected
ThreeZincAI
92%
Cost Reduction
5+
Cloud Providers
Open to opportunities
[Profile Image Placeholder]
◆ FEATURED CASE STUDY

ThreeZincAI

Workflow-driven AI Content Generation Platform

Built ThreeZincAI to help creative teams build, run and scale complex AI generation pipelines across images, shots and videos.

  • Visual workflow builder
  • Multi-stage generation pipelines
  • Asset lineage & version tracking
  • Distributed execution on GPU workers
  • Provider abstraction (FAL, Runware, Replicate, etc.)
  • History viewer
  • Canvas sharing
  • Real-time collaboration
Explore Case Study →
ThreeZincAI Node-Based Workflow Canvas
Image → Shots → Videos
[Perfume]
[Sports Car]
[Consistency]
[Interior]
[Vehicle]
[Landscape]
◆ FEATURED CASE STUDY

Carousely.ai

High-Volume Image Editing Optimization

Fine-tuned custom Qwen Image Edit LoRAs to optimize high-volume image editing pipelines. This architectural optimization reduced overall generation costs by 20x, saving hundreds of thousands of dollars annually while maintaining pixel-level text-to-image edit accuracy.

  • Custom Qwen Image Edit LoRA fine-tuning
  • 20x cost reduction compared to generic VLM APIs
  • Saved hundreds of thousands of dollars annually
  • Sub-second image editing latency
  • Custom dataset curation & alignment
Visit carousely.ai ↗
Visual Editing Pipeline & Cost Comparison
Standard VLM Pipeline$0.05 / edit
User PromptGeneric API VLMOutput
vs
Optimized LoRA Pipeline (dstack + Qwen)$0.0025 / edit (20x Cheaper)
User PromptQwen LoRA RouterSpot Instances
Annual Impact
Saved Hundreds of Thousands of $
Achieved 20x cost reduction for high-volume edit requests
◆ FEATURED CASE STUDY (FOUNDER)

DayZTools.ai

AI-Powered Game Development & Modding Suite

Founded and architected DayZTools.ai, a professional modding platform that helps game developers create 3D assets, pack PBO archives, and generate signed keys. Powered by custom dataset curation, WebGL preview frameworks, and generative AI nodes.

  • WebGL 3D Asset Builder & preview canvas
  • Instant PBO Modpacker with ZIP auto-binarization
  • Secure .bikey / .biprivatekey mod-signing suite
  • Generative loading screen & logo engines
  • Serving over 1,000+ active game developers and modders
Visit dayztools.ai ↗
WebGL 3D Asset Builder & Modding Interface
Platform Stats
Automated Game Asset & Mod Pipeline
Significantly reduces assets production time from hours to seconds
SYSTEM ARCHITECTURE

Distributed Inference Platform

ProducersAPI Clients
Global QueueCloudflare Workflows
OrchestratorModel Router
GPU Worker 1
GPU Worker 2
GPU Worker 3
StorageS3 / R2
Auto ScalingFault ToleranceRetries & BackoffLoad BalancingObservability
Architecture Diagram
User / Client
Workflow Engine
Job Queue
Worker Orchestrator
GPU Worker
GPU Worker
GPU Worker
GPU Worker
AI Providers (FAL / Replicate)
Asset Storage (S3 / R2)
IMPACT

GPU Infrastructure & Cost Optimization

Automatically spins up spot instances instead of expensive on-demand instances. By leveraging the dstack platform, the system dynamically orchestrates and provisions the cheapest spot instances available across continents from multiple platforms like RunPod, Vast.ai, AWS, Google Cloud, and Azure.

Before
100%
On-demand Baseline
After
7%
Spot Instances via dstack
93%
Cost Saved
What I Optimized
  • Spot instance orchestration
  • Dynamic workload placement
  • Multi-cloud failover
  • Auto-scaling GPU workers
  • Idle termination & cleanup
  • Intelligent retry & batching
Cost Over Time (Normalized)
Before After
100%
75%
50%
25%
0%
Week 1
Week 2
Week 3
Week 4
dstack Automated Spot GPU Procurement Flow
1
Workload Scale Request
Queue build-up triggers auto-scaler
2
dstack Orchestration
Fetches cheapest Spot configs
3
Multi-Cloud Search
RunPodVast.aiAWSGCPAzure
4
Spot Provisioning
Deploys instance at lowest rate
5
Cluster Registration
GPU worker joins active queue
MODEL ENGINEERING & CAPABILITIES

Generative AI Pipelines

CAPABILITIES

Custom Model Workflows

Specialized in configuring end-to-end generative pipelines—including Stable Diffusion XL, Flux, custom ControlNets, and IP-Adapter layers. Experienced in setting up high-precision models for identity preservation, character consistency, inpainting, and product photography enhancement.

SDXLFlux.1ControlNetIP-AdapterInpaintingCharacter Consistency
COMFYUI ARCHITECTURES

Custom Node Workflows

Select Workflow

Cloth Consistency Workflow

Maintains absolute clothing and outfit consistency across multiple generated frames, characters, and angles. Crucial for storytelling and visual continuity.

Outfit AlignmentIP-AdapterFluxTemporal Consistency
ComfyUI Node Graph Diagram
TECH STACK

Programming

PythonTypeScriptSQLBash

Infrastructure

DockerCloudflare WorkersCloudflare Durable ObjectsWebSocketsDistributed SystemsGPU Orchestration

Platforms

AWS / Azure / GCPRunpodVast.aidstackFAL / RunwareReplicate

AI / ML

Stable Diffusion / SDXLFluxLoRAControlNetIP-Adapter