AI Engineer with a focus on building intelligent, scalable systems across machine learning and large language models.

Graduated in Computer Science (Artificial Intelligence) with strong performance in core subjects including Machine Learning, Deep Learning, and Natural Language Processing. Alongside academics, accumulated 2.5+ years of hands-on industry experience working on applied AI systems, model deployment, and LLM-driven applications.

Work centers on designing end-to-end AI systems, from data pipelines and model development to deployment and optimization, with a focus on real-world impact rather than isolated experiments.

• Designing LLM-based systems using RAG, fine-tuning, and efficient inference techniques
• Building multi-agent and autonomous AI systems for research and task automation
• Developing applied AI solutions in domains such as healthcare and intelligent assistants

• Confidence estimation and reliability in neural networks
• Efficient training and optimization of large-scale models (QLoRA, quantization)
• Autonomous and self-improving AI systems
• Scalable architectures for LLM-based applications

Actively involved in research with published work and ongoing projects.

• Machine Learning and Deep Learning
• Natural Language Processing
• Large Language Models (LLMs)
• Applied AI Systems and Production ML
• Multi-agent Systems

Languages
Python, C++, Java, Go

AI / ML Frameworks
PyTorch, TensorFlow, scikit-learn, Keras

Data & Scientific Computing
NumPy, Pandas, SciPy

Backend & Systems
FastAPI, PostgreSQL, MongoDB

Cloud & Infrastructure
AWS, Google Cloud, Firebase

Tools
Git, GitHub, GitHub Actions

Open to collaboration in:

• AI/ML research and publications
• Advanced machine learning systems
• Open-source AI projects

LinkedIn: https://linkedin.com/in/royxlead
Email: royxlead@gmail.com