I will deploy ml model and llm as a production API

Turn your fine-tuned LLM, vision-language model, or custom AI pipeline into a fast, scalable, production-grade service. Serving open-weights models like Llama 3, Qwen 2.5, DeepSeek, or Mistral requires specialized inference engines, VRAM optimization, and low-latency infrastructure.

Whether you need a lightweight local setup or high-throughput cloud endpoints, I will wrap your model into an OpenAI-compatible API and deploy it to your preferred target platform.

What I Offer:

• High-Throughput LLM Serving: Deployment via vLLM, Ollama, TensorRT-LLM, or TGI for maximum generation speeds and batching
• API Development: OpenAI-compatible REST/WebSocket endpoints using FastAPI or vLLM native interfaces
• VRAM & Inference Optimization: Quantization (AWQ, GPTQ, BitsAndBytes, GGUF), KV-cache optimization, and LoRA adapter merging
• Serverless & Cloud Infrastructure: Scalable deployment on RunPod Serverless, Modal, AWS (SageMaker/EC2 GPU), GCP, or Hugging Face Spaces
• Containerization & MLOps: Production Docker builds with NVIDIA Container Toolkit runtime and automated CI/CD pipelines

Supported Models & Stacks:

Llama 3/3.1, Qwen 2.5, DeepSeek-R1/V3, Mistral/Mixtral, vLLM, Ollama, Hugging