I will build custom ai ml solutions using llm rag agents and data science

I'm an ML engineer who builds AI systems that actually work in production not weekend hacks or prompt-wrapper demos.

I work across the full modern AI/ML stack, so instead of hiring five different freelancers for five different pieces, you can bring the whole problem to me:

What I build:

AI Agents / Agentic Systems multi-step autonomous workflows, multi-agent architectures, task orchestration, tool-using agents built on Claude/GPT with real reliability (not just a chained prompt that breaks on edge cases).

LLM Integration custom LLM-powered features for your product: structured output pipelines, evaluation/reliability testing, prompt engineering that's actually validated for consistency, not guessed at.

RAG (Retrieval-Augmented Generation) chatbots and assistants grounded in your own data docs, PDFs, websites, knowledge bases with proper chunking and retrieval tuning, not generic defaults.

Reinforcement Learning custom RL environments and agents (PPO, SB3, Gymnasium), reward design, training pipelines, simulation environments.

Data Science end-to-end analysis, statistical modeling, predictive models, data pipelines, and clean visualizations that answer the actual business question.