Professional Overview
AI/ML Engineer building production-ready systems with LLMs, RAG, and machine learning. I help companies turn complex AI research into scalable solutions that solve real business problems. Expert in Python, PyTorch, LangChain, and cloud deployment. Current MEng candidate at UESTC researching multi-agent AI systems and offline self-improvement.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Researching offline self-improvement frameworks for LLM-based multi-agent.
- Building complete ML pipelines in Python/PyTorch: trajectory recording
- Evaluating models against state-of-the-art baselines in physical simulations
- Developing RAG systems with embeddings, vector search, and retrieval strategies.
- Fine-tuning Llama-3-8B via LoRA for multi-agent task planning and coordination.
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Researching offline self-improvement frameworks for LLM-based multi-agent.
- Building complete ML pipelines in Python/PyTorch: trajectory recording
- Evaluating models against state-of-the-art baselines in physical simulations
- Developing RAG systems with embeddings, vector search, and retrieval strategies.
- Fine-tuning Llama-3-8B via LoRA for multi-agent task planning and coordination.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
