
ML @ Skylark Labs | PyTorch • Computer Vision • Deep Learning
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Assessing your cultural and operational fit
tensorax
November 26, 2025 – Present
A pure C++/CUDA tensor library with zero PyTorch/NumPy dependencies. Complete autograd, PyTorch-like API. Built from scratch for deep learning.
View ProjectAutoUI
April 19, 2025 – September 10, 2025
Automated UI generator that creates Streamlit interfaces from natural language prompts using Google's Gemini API 🤖
View Projecttinygpt
April 7, 2025 – Present
🎈 A series of lightweight GPT models featuring TinyGPT Base (~51M params) and TinyGPT2 (~95M params). Fast, creative text generation trained on whimsical stories.
View ProjectDeepSeek-R1-Distill-Qwen-1.5B-SQL-Coder-PEFT
February 23, 2025 – February 25, 2025
DeepSeek R1 Distill Qwen 1.5B finetuned for converting natural language queries to SQL queries
View ProjectLoomRAG
December 27, 2024 – March 29, 2025
🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡
View ProjectQuillGPT
March 4, 2024 – February 1, 2025
Implementation of the GPT decoder block in PyTorch finetuned on Shakespeare's works 🪶
View ProjectIndian-Sign-Language-Classification-using-Transfer-Learning
March 4, 2023 – May 22, 2023
Indian Sign Language A-Z alphabets classification with Custom CNN and Resnet50
View ProjectMachine-Learning-from-Scratch
October 19, 2022 – April 3, 2023
ML / DL Algorithms implemented from scratch. Developed with only numpy as dependency. Machine Learning Algorithms such as Support Vector Machine, Linear Regression, Artificial Neural Networks and other data transformation algorithms are implemented. Project is released as a python package and can be download from Python Package Installer.
View Projectpydbops
July 6, 2022 – January 14, 2024
A Relational Database Management System. Developed on top of sqlite databases. CLI is included in the package. This project aims to provide more robust database management system for python android developers.
View ProjectSPPU-Computer-2019-Practicals
April 4, 2022 – April 26, 2024
All practicals I performed in Computer Engineering at SPPU
View ProjectCultural Fit Analysis
The candidate demonstrates a strong passion for personal projects and self-directed learning, which aligns well with an innovative and growth-oriented culture. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration and broader cultural fit. The projects are highly relevant to the target role, indicating strong intrinsic motivation.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are clear and concise, indicating good technical communication.