Final-year CSE (AI/ML) student and ex-NetApp ML intern. I build forecasting systems, backend services, and the occasional Rust CLI — shipping things that turn messy data into decisions.
S/S
PORTRAIT · PENDING
PROFILE
I'm Shrey — a final-year B.Tech CSE (AI/ML) student at Manipal Institute of Technology. Most recently I spent six months as an ML intern at NetApp, Bengaluru — building revenue forecasting and commission regression systems used by sales and finance teams.
I work across ML and systems. Time-series and regression on one side; Go, Rust, and backend services on the other. I like problems where the data won't sit still — seasonality, missingness, regime shifts — and code that earns its place in production.
Outside work I grind algorithms on LeetCode (1756, top 15%) and NeetCode, keep a small Kaggle presence, and build things in languages I don't strictly need to learn — mostly because it's fun.
FACTS
Forecasting systems, backend infrastructure, and experiments I couldn't not ship. Two used in production; three on GitHub.
End-to-end forecasting pipeline predicting $1B+ in revenue across 1.5M+ records. Cleaning, feature engineering, anomaly detection, and smoothing for irregular, high-stakes time series — consumed directly by finance and planning.
WHEN
JUN 2025 — DEC 2025
TOOLS
OUTCOME
$1B+ predicted
Ensemble regression forecasting commissions for 4,900+ users. 60+ engineered features — lags, seasonality, rolling stats — with hyperparameter tuning and automated reporting pipelines.
WHEN
JAN 2026 — MAR 2026
TOOLS
OUTCOME
6–10% MAPE
What I reach for. ML first, but equally at home in backend and systems work.
Python, Go, Rust, C++, SQL, JavaScript / TypeScript.
PyTorch, Scikit-learn, XGBoost, LightGBM, Pandas, NumPy, OpenCV.
FastAPI, React, Node, PostgreSQL, MongoDB, Redis.
Docker, Git, Linux, CI/CD, Airflow, AWS basics.
Open to full-time ML and backend roles starting 2026. Also happy to talk forecasting, Rust, or a good pipeline.
