Professional Overview
Business & Executive Leadership: Company Strategy & Vision, P&L and Budget Ownership, Client & Stakeholder Relations, Business Development, Team Leadership & Hiring, Product Roadmap Ownership, Cross-Functional Program Management, Go-to-Market Strategy, Technology Commercialization AI/ML Engineering: Python, PyTorch, LLMs (Claude, GPT, LLaMA, DeepSeek, Groq) & VLMs (CLIP, LLaVA-Med, Qwen-VL, MedGemma), Fine-Tuning (Unsloth, HuggingFace, LoRA/QLoRA), Multi-Agent Systems (AutoGen, LangChain, n8n), RAG (Pinecone, Qdrant), Real-time Voice AI (Twilio, DeepGram, ElevenLabs, Whisper), Deep Learning (CNN, RNN/LSTM), AWS (EC2, S3, SageMaker), CI/CD (Docker, GitHub Actions)
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.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
