Building practical AI solutions by combining Machine Learning, Deep Learning, LLM-based reasoning, and a strong Engineering mindset.
📍 Based in The UAE · Open to opportunities in AI/ ML Engineering, Generative AI, and AI Architecture
- 🎓 Master of Science in Artificial Intelligence (AI) and Machine Learning (ML).
- 📜 Certified in Machine Learning (ML) and Artificial Intelligence (AI).
- 🤖 I bring 2+ years of ML engineering experience alongside 14+ years in Software testing and Performance engineering.
- 🧠 Interested in Gen AI, Large Language Models (LLMs), AI Agents, Tool-augmented reasoning, Production-ready ML systems.
- 🔬 Academic research on: Improving Tool-use efficiency in LLM-based AI Agents, including Chain-of-Abstraction (CoA) reasoning.
- 🏗️ Working on to design reliable, scalable AI systems with an focus on eval, performance, maintainability, responsible deployment.
- 🌍 Based in the United Arab Emirates (UAE) and interested in opportunities where AI can solve meaningful business problems.
- 🚀 I bring together an AI/ ML learning and building mindset with years of experience in quality, performance, and systems thinking.
- Machine Learning · Deep Learning · Model Evaluation
- Generative AI · Large Language Models (LLMs) · Prompt Engineering
- AI Agents · Tool-Augmented Reasoning · Chain-of-Thought (CoT) / Chain-of-Abstraction (CoA) concepts
- Natural Language Processing (NLP) · Computer Vision
- Python · SQL
- Pandas · NumPy · SciPy · scikit-learn
- Matplotlib · Seaborn · Jupyter Notebook
- PyTorch · TensorFlow
- Hugging Face Transformers
- MLflow · Git · Docker
- AWS and Microsoft Azure (currently developing cloud skills)
- Performance Testing · Software Quality Engineering
- Test Planning · Troubleshooting · Root-Cause Analysis
- Performance Analysis · Reliability and scalability thinking
My academic interests include making LLM-powered systems more effective at using tools and solving multi-step tasks.
- LLM Agents: planning, reasoning, and tool selection.
- Chain-of-Abstraction (CoA) reasoning: separating high-level reasoning from tool execution.
- Evaluation: task accuracy, latency, and tool-call efficiency.
- Experimentation: comparing reasoning and tool-use approaches on question-answering and mathematical reasoning tasks.
- M.Sc in AI and ML (On-line) — Liverpool John Moores University (LJMU), Liverpool, UK
- Executive Post Graduate Program (ePGP) in ML and AI (On-line) — International Institute of Information Technology-Bangalore (IIIT-B), India
- B.Tech in Computer Science — Jawaharlal Nehru Technological University (JNTU), Hyderabad, India
- Machine Learning Engineering: 2+ years of experience, supported by postgraduate study and project work in AI/ ML.
- Software Testing & Performance Engineering: 14+ years of experience in enterprise environments, including performance testing, analysis, and troubleshooting.
- Mainframe Development: earlier experience in enterprise application development.
This background helps me approach AI systems with attention to measurable performance, robustness, testing, and operational quality.
I'm interested in connecting with AI/ ML practitioners, Researchers, Hiring teams, and Technology leaders across the UAE.
- GitHub: SurendranathDuvvuru
- LinkedIn: surendranathduvvuru
Learn continuously. Build thoughtfully. Measure what matters. Create AI that helps.