Building systems that think, reason and ship.
AI Engineer focused on agents, retrieval, and real-world systems - reasoning, retrieving, automating, and scaling.
Download CVCurrently
Building
What I reach for - chosen because it ships, not because it's trendy.
2025
Machine Learning Intern
Sleep-disorder prediction · 87% accuracy · Python, Scikit-learn
2026
AI Engineer Intern
3+ LLM apps & agents · 200+ users · RAG, LangChain
Next
Open to AI Engineering roles
Let's build something.
2025
Machine Learning Intern
Sleep-disorder prediction · 87% accuracy · Python, Scikit-learn
2026
AI Engineer Intern
3+ LLM apps & agents · 200+ users · RAG, LangChain
Next
Open to AI Engineering roles
Let's build something.
Selected highlights
Education
CGPACredentials
Recent thoughts - short notes from building things.
It's retrieval quality, not model size, that decides whether the answer is useful.
Users feel p95 latency. They never see your benchmark scores.
Guardrails, evals, and knowing when the agent should stop.
If you can't measure it, you can't improve it - agents especially.
Be precise about the contract, not clever with the words.
roger@demello:~$ contact
status:Open to AI Engineering roles
Fell for the math behind ML.
An electronics undergrad who got pulled into models, gradients, and messy real data.
Built ML systems.
Sleep-disorder prediction at 87% accuracy - feature engineering, validation, the boring parts that matter.
Started building agents.
Shipped 3+ LLM apps and autonomous agents to 200+ users at AI LifeBOT.
Obsessed with making AI useful.
RAG that actually retrieves, agents that actually finish the task.
How I work
