shubhamsarkarthe1@gmail.com
Hi, I'm Shubham

I create innovative AI solutions that enhance performance and drive project success.

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I'm Shubham Sarkar, a Full Stack Developer
Shubham Sarkar

I'm Shubham Sarkar, a detail-oriented Machine Learning Engineer with expertise in deep learning, NLP, and computer vision. I thrive in cross-functional teams, delivering scalable AI solutions that meet project goals and push the boundaries of technology.

My Journey

Machine Learning Engineer @Alignerr

Jan 2026 – Present · Remote
  • Enhanced LLM evaluation precision by 15% through a comprehensive review of a rubric-based scoring framework across six reasoning categories.
  • Analyzed over 50 audio files for integration into ASR pipelines.
  • Evaluated AI agent responses, identifying failure points such as inference memory and self-coherence, resulting in a 20% improvement in model accuracy.

Deep Learning Research Assistant @Jadavpur University CMATER Lab

May 2025 – September 2025 · Kolkata, India
  • Designed and implemented a self-attention mechanism (scaled dot-product) within a pre-trained VGG16, significantly enhancing feature extraction for lung cancer detection from CT scans.
  • Developed a hybrid deep learning architecture achieving 99.54% peak accuracy with only 76k trainable parameters and 0.0256 GFLOPs, facilitating edge-device deployment.
  • Engineered feature fusion through concatenation and element-wise multiplication of original and attention-modulated maps for refined, context-aware representations.

Bachelor of Technology

Jadavpur University, Kolkata (Nov 2023 – Dec 2027) · CGPA: 7.5

Higher Secondary

Hariyana Vidya Mandir, Kolkata (Apr 2020 – Apr 2022) · Percentage: 90%

Skills & Tools

Machine Learning 78%
Deep Learning 83%
Natural Language Processing (NLP) 93%
Computer Vision 71%
LLM Fine Tuning 71%
RAG 91%
TensorFlow 88%
PyTorch 93%
scikit-learn 76%
Hugging Face 76%
Pandas 86%
NumPy 79%
Langchain 81%
Flask 79%
FastAPI 93%
Amazon Web Services (AWS) 89%
Docker 86%
MLflow 86%
DVC 91%
Streamlit 81%
CI/CD 79%
PostgreSQL 88%
SQL 91%
ETL Pipelines 83%
Linux 79%
Vector Databases (Chroma) 89%
Python 86%
C 77%
JavaScript 88%
HTML 72%
CSS 91%
Data Structures and Algorithms 72%

Projects

Some of the things I've built.

TailorCV.ai

TailorCV.ai

  • Developed an AI web application that optimizes resumes to job descriptions using LLMs and NLP pipelines, improving resume relevance by up to 80%.
  • Designed a Python and FastAPI backend with HTML, CSS, and JavaScript for the frontend, dockerized the application, and deployed it on AWS ECS.
  • Achieved over 50 users within the first week of launch, demonstrating strong early adoption and real-world impact.
PythonFastAPILLMAI agentsAmazon Web Services
Live Demo GitHub
YouTube Sentiment Analysis

YouTube Sentiment Analysis

  • Created an end-to-end YouTube sentiment analysis pipeline processing over 10,000 user comments, enhancing sentiment classification performance through NLP preprocessing techniques.
  • Tracked multiple model experiments using MLflow and DVC, enabling reproducible training and systematic comparison of models built with scikit-learn and NLP libraries.
  • Deployed the pipeline on AWS using Docker and exposed predictions via Flask REST APIs, facilitating scalable and reproducible inference.
TensorFlowNLPAWS EC2Scikit-learn
Live Demo GitHub
Smart Product Pricing

Smart Product Pricing

  • Developed an NLP and CV pipeline to analyze 150,000 image and text data using transformer-based text encoders and CNN-based image embeddings, integrating them through a fusion neural network for price prediction.
  • Implemented data preprocessing techniques, including text cleaning, tokenization, and streaming image feature extraction with ResNet and CLIP representations to manage large datasets.
  • Built and fine-tuned models using TensorFlow and scikit-learn, achieving a rank of 142 out of 50,000 participants.
KerasHugging Face TransformersResNet50OpenCV
GitHub
RAG System

RAG System

  • Made a production-ready RAG pipeline integrating semantic vector retrieval with LLM generation to produce context-grounded responses.
  • Engineered multiple chunking strategies and a scalable ingestion , retrieval , generation flow for efficient semantic search and generation.
  • Implemented history-aware and multimodal augmentations, and evaluated retrieval outputs to measure relevance and quality.
GitHub

Open Source & Leadership

Core Member @Entrepreneurship Cell, Jadavpur University

May 2024 – Present
  • Organized national-level events such as E-Summit 2025 and Hult Prize 2025, attracting over 5,000 registrations and 1,000+ attendees.
  • Contributed to the establishment of an Incubation Center at Jadavpur University under the Institution’s Innovation Council (IIC).

Get In Touch

Let's discuss your next project or just say hello!

Let's Connect

I'm always open to discussing new opportunities, interesting projects, or just having a chat about technology and development.

Email
shubhamsarkarthe1@gmail.com
Location
36/F Sitalatala Lane, Kolkata, 700011
Response Time
Within 24 hours