saarthak
solving generative engine optimization
I'm Saarthak, an ML engineer exploring generative model optimization. I've worked on classical DL, GNNs, and NLP. Check out my posts section :)
what i do
ML Engineer • Startup (Contract)
Jun 2025 - Nov 2025 (Contract work: Jul 2025 - Oct 2025)
- Business Impact: Built the core ML infrastructure that helped the client secure a ₹30 Lac (~$35k) research grant.
- Custom Tooling: Adapted and extended GraphGym source code to ingest custom molecular embeddings, enabling automated experimentation across 48k data points.
- Massive Scale: Orchestrated 1,000,000+ optimization trials on remote distributed GPUs and beat Chemprop, the industry standard.
- Rapid Delivery: Shipped a production-ready, lightweight (2M param) inference API in 8 weeks, handling the full lifecycle from data ingestion to AWS deployment using FastAPI and Docker.
Software Engineering Intern • HeydoTech
Jan 2024 - May 2024
- Utilized Python libraries including OpenCV and PyAutoGUI to develop 2 automation tools for internal projects
- Collaborated with cross-functional teams of 5+ members to implement feature enhancements, improving system performance for approximately 100 users
- Contributed to UI/UX improvements that enhanced overall user experience, as measured by positive feedback from 80% of test users
projects
Docbook
- GraphRAG-based CLI tool for intelligent documentation context extraction
- Single URL input to full knowledge graph conversion using crawl4ai
- Automated semantic search and retrieval system
Bayesian Course Recommendation System
- Achieved 0.915 AUC using Bayesian Personalized Ranking for implicit feedback
- Implemented matrix factorization with BPR optimization
- Handles cold-start problem with probabilistic inference
education
BTech, ECE
IIIT Delhi
Nov 2022 - Present
what excites me
I'm spending most of my time diving into NLP these days to solve generative engine optimization from first principles as an LLM research problem.
There's something fascinating about how we can influence LLMs for particular websites, and I'm here to solve it.
let's connect
Want to discuss AI, collaborate on projects, or just chat about tech? Feel free to reach out!
posts
Graph Neural Networks from Scratch
A comprehensive exploration of Graph Neural Networks — from ground up. Covering everything from how to represent Graph to how contraction mapping gurantees convergence in training of GNN.
Read post →Bayesian Personalized Ranking
Exploring the fundamentals of Bayesian Personalized Ranking for implicit feedback systems. Breaking down the math, intuition, and implementation details behind one of the most elegant recommendation algorithms.
Read post →Bayesian Linear Regression
A deep dive into Bayesian approaches to linear regression. Understanding posterior distributions, conjugate priors, and how Bayesian inference provides uncertainty quantification unlike traditional least squares methods.
Read post →