ML Systems Engineer | Agentic AI platforms | CUDA/PyTorch kernels | LLM inference
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Inference-Kernels
June 17, 2026 – Present
LLM inference kernels from scratch in Triton: KV cache, FlashAttention, PagedAttention, RMSNorm, RoPE, SwiGLU, and benchmarks.
View ProjectDSBDA-MiniProject
April 28, 2022 – May 16, 2022
This repository serves as DSDBA Mini-Project.
View ProjectSemantic-Segmentation-using-U-Net
April 14, 2022 – April 14, 2022
Implementing Semantic Segmentation on Satellite images using U-Net architecture
View ProjectDecentragram
December 27, 2021 – December 27, 2021
This application is a decentralized version of instagram build using Ethereum & Metamask.
View ProjectMachine-Learning-Collection
December 20, 2021 – February 9, 2025
Repo for Implementing Research Papers & Projects related to Machine Learning
View ProjectBloodCell-Detection-Datatset
October 4, 2021 – October 4, 2021
This is a dataset of blood cells photos.
View ProjectHealthCare-Management-System
February 14, 2021 – February 14, 2021
A DBMS application which can be used by hospitals, clinics and healthcare centres to manage records for patients, doctors, prescriptions, medical tests and various departments.
View ProjectModelling-and-simulation-for-one-day-cricket
December 10, 2020 – December 10, 2020
Given that only a finite number of outcomes can occur on each ball that is bowled, a discrete generator on a finite set is developed where the outcome probabilities are estimated from historical data involving one-day international cricket matches. The probabilities depend on the batsman, the bowler, the number of wickets lost, the number of balls bowled and the innings. The proposed simulator appears to do a reasonable job at producing realistic results.
View ProjectParkinsons-DiseaseDetection
July 9, 2020 – July 5, 2021
In this Python machine learning project, using the Python libraries scikit-learn, numpy, pandas, and xgboost, I have build a model using an XGBClassifier. We’ll load the data, get the features and labels, scale the features, then split the dataset, build an XGBClassifier, and then calculate the accuracy of our model.
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards data science and machine learning, which aligns with a Data Scientist role. The diversity of projects, from sports analytics to healthcare and deep learning, indicates a broad interest in applying data science techniques. However, all projects are personal, which limits insight into team collaboration or professional work environments.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise but do not provide insight into collaboration, problem-solving approaches, or communication style.