Need LLM integration that scales? I provide LLM integration, fine-tuning, and custom model development. FastAPI, Django, LangChain, and production deployment pipelines. Your LLM application, deployed and working.
Need LLM integration that scales? I provide LLM integration, fine-tuning, and custom model development. FastAPI, Django, LangChain, and production deployment pipelines. Your LLM application, deployed and working.
Multi-model expertise
OpenAI, Anthropic, open-source models
Production deployment
Scalable LLM applications
Expert LLM integration and fine-tuning services with production-ready deployments and comprehensive documentation.
Clear outcomes, the right guardrails, and async updates while we work.
Availability: 1–2 concurrent builds max.
Timeframe: Typical engagement 6–10 weeks.
Collaboration: Weekly demos, shared roadmap, <24h async response.
How we break down the work so you stay unblocked at every phase.
Integrated multiple LLM providers (OpenAI, Anthropic, Cohere) with fallback mechanisms and cost optimization. Includes rate limiting, caching, and response streaming.
Fine-tuned Llama-2, GPT-3.5, and custom models on proprietary data using LoRA and QLoRA. Achieved 40% improvement in domain-specific tasks with reduced hallucinations.
Built autonomous agent systems with LangChain and LlamaIndex. Features include tool use, memory management, multi-agent collaboration, and self-correction mechanisms.
Implemented semantic search with Pinecone, Weaviate, and ChromaDB. Includes chunking strategies, hybrid search, metadata filtering, and reranking.
Deployed production LLM services with FastAPI, load balancing, request queuing, and cost monitoring. Handles 10M+ requests/month with 99.9% uptime.
Founders and operators keeping us honest.
Built our LLM integration—handles 10K requests/day.
Shubham integrated LLMs into our product with RAG architecture. The system handles 10K requests per day seamlessly. He set up proper error handling, rate limiting, and monitoring. Production-ready from day one.
MLOps pipeline reduced our model deployment time by 80%.
We were manually deploying ML models. Shubham built an MLOps pipeline with automated training, versioning, and deployment. Model deployment time went from days to hours. The monitoring and alerting he added caught issues early.
Fine-tuned our LLM model—accuracy improved 25%.
Shubham fine-tuned our LLM model for our specific use case. Accuracy improved by 25%, and inference time stayed the same. He also built the API and monitoring infrastructure. Great work.
I specialize in machine learning, deep learning, LLM integration, computer vision, and MLOps. I work with TensorFlow, PyTorch, FastAPI, Django, and production deployment pipelines.
I offer AI model development, LLM integration, computer vision solutions, MLOps pipeline setup, and AI consulting. Available for contract and hourly work. Contact me to discuss your AI project needs.
I start by understanding your AI requirements and data, then design and develop models tailored to your needs. I focus on production-ready solutions with proper MLOps pipelines, monitoring, and documentation.
I have experience deploying AI models to production using FastAPI, Django, Kubernetes, AWS SageMaker, and MLflow. I ensure models are scalable, monitored, and maintainable in production environments.