Professional Overview
I am a Lead AI/ML Engineer with 9+ years of experience building production-ready AI systems, specializing in Generative AI, LLMs, RAG, AI agents, NLP, computer vision, and MLOps. I design scalable AI solutions using Python, cloud platforms, and modern ML frameworks to transform complex problems into impactful products.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built production RAG, LLM, and multi-agent AI systems.
- Designed scalable ML pipelines, APIs, and cloud deployments.
- Led model evaluation, monitoring, guardrails, and MLOps.
- Integrated AI workflows with databases and third-party APIs.
- Guided teams and clients from architecture to delivery.
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built ML, NLP, and computer vision solutions for real-world use.
- Developed Python pipelines for data prep, training, and validation.
- Deployed models through APIs for reliable product integration.
- Improved model performance through tuning, testing, and monitoring.
- Turned business needs into practical, production-ready AI features.
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built data pipelines for high-quality, ML-ready datasets.
- Engineered features and validated models using Python and SQL.
- Developed predictive models for business and operational insights.
- Integrated ML outputs into APIs and internal software workflows.
- Improved reliability through testing, monitoring, and documentation.
Education
Field of Study: Artificial Intellegence
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
