I will build mlops pipeline and deploy ml llm models on gpu runpod with mlflow

I deploy all types of ML and LLM models including machine learning, deep learning, NLP, GenAI, RAG systems, GPT, Llama, Mistral and fine-tuned LLMs. Whether it's a classification model, transformer, or open-source LLM, I'll deploy it to production with MLOps best practices for scalability.

Yes, I offer LLM fine-tuning using LoRA and QLoRA on Hugging Face for models like Llama, Mistral and GPT. I also build production-ready RAG pipelines with LangChain and vector databases such as Pinecone, FAISS or Weaviate. Perfect for chatbots, document Q&A, and custom AI assistants.

I work with all major MLOps tools including MLflow, Kubeflow, Airflow, FastAPI and BentoML. For cloud deployment, I use AWS SageMaker, Google Vertex AI, Azure Machine Learning and Databricks. For GPU-based LLM deployment, I work with RunPod, Modal and Vast.ai.

Yes, I set up complete model monitoring including performance tracking, drift detection and automated alerts using MLflow. I also build automated retraining pipelines that retrain your models on new data, ensuring your ML system stays accurate in production.

Absolutely! I deploy LLMs on GPU cloud platforms like RunPod, Modal and Vast.ai for cost-effective, scalable inference. I use vLLM, Ollama and Hugging Face Text Generation Inference for high-performance LLM serving with optimized GPU utilization and auto-scaling for production workloads.

Basic ML model deployment takes 3 days, while a complete end-to-end MLOps pipeline with monitoring and retraining takes 5 days. Full MLOps and LLMOps solutions with fine-tuning, RAG and multi-cloud deployment take 7 days. Timelines depend on your project scope, let's discuss for accuracy.

You'll receive complete source code, deployed ML/LLM models with API endpoints, MLflow tracking dashboard, monitoring setup and full technical documentation (Premium tier). All code is production-ready, well-commented and follows MLOps best practices so you or your team can easily maintain it.

Yes! Standard package includes 3 days post-delivery support, and Premium includes 7 days plus full technical documentation covering pipeline architecture, model deployment steps and maintenance guidelines. I'm here to help troubleshoot, answer questions and ensure your MLOps system runs smoothly.