You will get Deploy and Optimize an Enterprise LLM Platform On-Site or in the Cloud


Project details
I help organizations deploy reliable and secure Large Language Model platforms either on-premises or in the cloud. With 25+ years of Linux, DevOps, and infrastructure experience — plus hands-on work with GPUs, Kubernetes, MLOps, and secure CI/CD — I deliver production-ready AI systems that scale.
Your project will benefit from expert-level design and deployment of LLM runtimes such as vLLM, TGI, HuggingFace, or custom fine-tuned models. I build complete inference pipelines with APIs, monitoring, logging, role-based access, and automated deployment workflows.
Whether you need a private, compliance-ready LLM environment or a cloud-based solution optimized for performance, I ensure the platform is stable, fast, secure, and fully documented. My focus is to give you an AI infrastructure that is simple to operate and ready for real workloads.
Your project will benefit from expert-level design and deployment of LLM runtimes such as vLLM, TGI, HuggingFace, or custom fine-tuned models. I build complete inference pipelines with APIs, monitoring, logging, role-based access, and automated deployment workflows.
Whether you need a private, compliance-ready LLM environment or a cloud-based solution optimized for performance, I ensure the platform is stable, fast, secure, and fully documented. My focus is to give you an AI infrastructure that is simple to operate and ready for real workloads.
AI Algorithms
Transformer ModelAI Applications
AI Chatbot, AI Text-to-Image, AI Text-to-SpeechAI Development Language
PythonAI Tools
Azure OpenAIAI Models
LLaMAWhat's included
| Service Tiers |
Starter
$500
|
Standard
$2,000
|
Advanced
$4,500
|
|---|---|---|---|
| Delivery Time | 3 days | 15 days | 25 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
About Omer F
Principal DevOps/MLOps Consultant
London, United Kingdom - 9:19 am local time
Steps for completing your project
After purchasing the project, send requirements so Omer F can start the project.
Delivery time starts when Omer F receives requirements from you.
Omer F works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements & Architecture Planning
I review your goals, data, compliance needs, deployment preference (on-prem or cloud), and design the optimal LLM architecture.
Infrastructure & Environment Setup
I prepare cloud or on-site GPU infrastructure, networking, storage, Python/MLOps tooling, and environment needed for LLM deployment.