Applied AI · Recommender systems · Austin, TX
I build intelligence into products.
I’m Vivek, a machine learning practitioner working at the intersection of product recommendations, generative AI, and real human behavior.
How agents remember, recommend, and make better decisions.
01 / Perspective
The best AI products don’t feel like a model demo. They feel attentive, useful, and inevitable.
My work connects rigorous machine learning with product intuition: understanding the person, the moment, and the next useful action.
02 / Selected work
Things I’m building.
A living collection of prototypes, technical explorations, and practical tools.
macOS app · 2026
Attune
A real-time attention feedback layer for children’s learning — on-device webcam sensing that nudges focus back during homework, without recording or uploading video.
- Swift
- Core ML
- On-device
Interview prep · 2026
Work Simulator
Makes interview prep feel alive — simulates a real work environment with teammates, tickets, and tradeoffs instead of grinding LeetCode.
- TypeScript
- AI agents
- Interview prep
Crash course · 2026
AI Crash Course for Product Managers
A fast, practical primer on modern AI for PMs — enough technical depth to ship informed product decisions without becoming an engineer.
- AI product
- Product managers
- Interactive web
ML system · 2025
Ranker
A practical exploration of ranking: turning noisy candidate sets into ordered, relevant, and useful recommendations.
- Python
- Ranking
- Recommendations
03 / Field notes
Thinking in public.
Notes on applied AI, recommendation systems, and what I learn while building.
Conversational AI · 6 min
Building conversational AI with memory
Semantic, episodic, and procedural memory in practice. ↗Recommender systems · 1 min
Transformers4Rec: the TL;DR version
A quick path from interaction data to sequential recommendations. ↗More soon
Follow the notebook
Experiments become notes. Notes become better experiments. ↗
Vivek Praturi
Austin, Texas
04 / About
Builder by instinct.
Scientist by training.
I work in machine learning and generative AI, with a focus on product recommendations at Nike.
I’m interested in systems that learn from behavior without losing sight of the human behind the data. Outside my day job, I build small, opinionated projects to test ideas quickly and share what holds up.
Recommendations, GenAI, applied ML
Masters in AI · UT Austin
Prototype, measure, explain, repeat
05 / Let’s connect
Have an interesting
problem in mind?
I’m always glad to talk about recommendation systems, applied AI, product ideas, and ambitious experiments.