class MLEngineer:
def __init__(self):
self.name = "Anupam Hegde"
self.role = "ML Engineer & GenAI Developer"
self.location = "Bengaluru, India 🇮🇳"
self.interests = ["AI Agents", "Deep Learning",
"Computer Vision", "NLP", "RAG Systems"]
self.current_focus = "Building production-ready GenAI applications"
self.coffee_consumed = "∞"
def say_hi(self):
print("Thanks for dropping by! Let's build something amazing together!")
me = MLEngineer()
me.say_hi()🔥 Passionate about leveraging Machine Learning and Generative AI to solve real-world problems
💡 Currently exploring Prompt engineering, and agentic AI workflows
🌱 Learning RAG architectures and multimodal AI systems
🎓 Mission Creating AI solutions that make a tangible impact
- 🚀 Building: Multi-agent RAG system with LangGraph
- 📚 Learning: Advanced prompt engineering & LLM optimization
- 🎯 2026 Goal: Contribute to 5+ open-source AI projects
- 💬 Ask me about: LangChain, Machine Learning, RAG, Vector DBs
- ⚡ Fun fact: I debug faster with coffee ☕ and lo-fi music 🎵
Python ████████████████████░░░ 85.2%
JavaScript ██░░░░░░░░░░░░░░░░░░░ 8.5%
Markdown █░░░░░░░░░░░░░░░░░░░░ 4.1%
YAML ░░░░░░░░░░░░░░░░░░░░░ 2.2%
"Any sufficiently advanced technology is indistinguishable from magic."
— Arthur C. Clarke
"The question of whether a computer can think is no more interesting than the question of whether a submarine can swim."
— Edsger W. Dijkstra
I'm always excited to collaborate on innovative ML/AI projects, especially those involving:
🤖 Generative AI applications | 🧠 LLM fine-tuning & optimization
📊 End-to-end ML pipelines | 🔍 RAG systems & knowledge retrieval
Open to: Collaborations • Freelance Projects • Research Opportunities • Open Source Contributions