Dr. Charalambos Theodorou

AI Researcher / Engineer | Machine Learning Expert | Entrepreneur | Investor

Pioneering advances in artificial intelligence and machine learning, from large language models and neural networks to intelligent agents that shape the future.

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Dr. Charalambos Theodorou

About Me

As a researcher and practitioner in artificial intelligence and machine learning, I focus on developing intelligent systems that push the boundaries of what's possible from large language models to autonomous agents and deep reinforcement learning architectures.

AI Research & Development

Conducting cutting edge research in deep learning, neural network architectures, and reinforcement learning to advance the state of artificial intelligence.

LLMs & AI Agents

Specializing in large language models and intelligent agent systems that can reason, learn, and adapt to complex real-world scenarios.

Applied Machine Learning

Translating theoretical advances into practical solutions that solve challenging problems across industries using state-of-the-art ML techniques.

Core Expertise

Python & LLM Engineering

  • Python (Expert Level - Primary Language)
  • LLM Fine-tuning & RLHF
  • Prompt Engineering & Chain-of-Thought
  • RAG (Retrieval-Augmented Generation)
  • LangChain, LlamaIndex, Hugging Face
  • GPT-4, Claude, LLaMA, Mistral

AI Agents & Autonomous Systems

  • Autonomous AI Agent Development
  • Multi-Agent Systems & Coordination
  • Agentic Workflows & Tool Use
  • Agent Evaluation & Benchmarking
  • AutoGPT, BabyAGI, CrewAI Patterns
  • Function Calling & API Integration

AI Safety & Research

  • Red-Teaming & Adversarial Testing
  • Model Alignment & Constitutional AI
  • Safety Evaluation Frameworks
  • Jailbreak Detection & Mitigation
  • AI Governance & Policy Compliance
  • Research Publication & Patent Development

ML/DL Frameworks & Infrastructure

  • PyTorch, TensorFlow, JAX
  • Transformer Architectures (BERT, GPT, T5)
  • Deep Reinforcement Learning (PPO, DQN)
  • MLOps & Model Deployment
  • AWS SageMaker, Azure ML, GCP Vertex AI
  • Docker, Kubernetes, CI/CD for ML

NLP & Generative AI

  • Natural Language Processing
  • Text Generation & Summarization
  • Sentiment Analysis & Classification
  • Named Entity Recognition (NER)
  • Semantic Search & Embeddings
  • Multimodal AI (Vision + Language)

Data Science & Engineering

  • SQL, NoSQL, Vector Databases
  • Data Pipeline Engineering (ETL/ELT)
  • Feature Engineering & Selection
  • A/B Testing & Experimentation
  • Statistical Analysis & Modeling
  • Data Visualization (Plotly, Matplotlib)

Work Experience

Lead AI Researcher / Engineer

Sept 2024 - Present

Fountech AI

  • Led cross-functional teams of 31 engineers/researchers delivering production AI systems from scratch
  • Developed LLM/Transformer solutions for generative AI, multimodal models, and agentic workflows
  • Executed red-teaming and adversarial evaluation to identify jailbreaks and policy bypasses
  • Improved model alignment via preference tuning, prompt optimization, and safety-first engineering
  • Built evaluation harnesses for safety, robustness, and quality metrics supporting release governance

Tech: Python, LLMs/Transformers, RAG, AI Safety & Alignment, Prompting

Machine Learning Engineer - CTO

Feb 2021 - 2024

Briteyellow

  • Led ML + LLM systems from prototype to production, saving $500K+ while improving outcomes
  • Built NLP/LLM solutions (LLaMA, GPT-3) with structured prompting and model optimization
  • Owned AI safety workstreams: red-teaming, policy-aligned prompting, automated evaluation
  • Deployed scalable inference pipelines on AWS & Azure, cutting deployment time 30%
  • Shipped recommender systems increasing engagement 20% and sales 25%
  • Developed novel vSLAM framework; published 4 papers and contributed to 5 patents

Tech: Python, PyTorch, TensorFlow, LLMs (LLaMA, GPT-3), AWS, Azure, Docker/Kubernetes

Machine Learning Engineer - NLP

Sept 2017 - Aug 2018

ImpacTech

  • Built end-to-end NLP pipeline for call analytics with sentiment analysis and keyword spotting
  • Deployed sentiment classification models for real-time insights across customer interactions
  • Improved model accuracy +8% through feature engineering and iterative optimization
  • Developed compliance flagging model for AI safety and policy violation detection

Tech: Python, NLP (spaCy, NLTK), scikit-learn, Speech-to-Text

Education

Doctorate (Ph.D.) in Artificial Intelligence & Machine Learning

University of Bedfordshire

Advanced research in deep learning architectures, reinforcement learning algorithms, and intelligent agent systems. Contributed novel approaches to neural network optimization and multi-agent coordination.

Master's Degree in Data Science & Machine Learning

University of Bath

Specialized in statistical learning theory, neural networks, and computational intelligence. Developed expertise in deep learning frameworks and large-scale model training.

Bachelor's Degree in Computer Science & Mathematics

University of Kingston London

Strong foundation in algorithms, data structures, mathematics, and artificial intelligence fundamentals with honors distinction.