Shubham Sarkar AI portfolio

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Shubham Sarkar's AI portfolio · answers are generated from their resume.

Shubham Sarkar — Machine Learning Engineer

I'm Shubham Sarkar, a results-driven Machine Learning Engineer with a passion for Deep Learning and NLP. I thrive on enhancing model performance and deploying impactful AI solutions that tackle complex challenges and push the boundaries of technology.

Skills

Languages: SQL
Python
C
JavaScript
HTML
CSS
AI/ML: Machine Learning
Deep Learning
Computer Vision
LLM Fine Tuning
RAG
Frameworks/Libraries: Natural Language Processing (NLP)
TensorFlow
PyTorch
scikit-learn
Hugging Face
Pandas
NumPy
Langchain
Flask
FastAPI
Amazon Web Services (AWS)
Streamlit
ETL Pipelines
Data Structures and Algorithms
Databases: PostgreSQL
Vector Databases (Chroma)
Tools & Platforms: Docker
MLflow
DVC
CI/CD
Linux

Experience

Machine Learning Engineer — Alignerr Jan 2026 – Present

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, leading to a 20% improvement in model accuracy.

Deep Learning Research Assistant — Jadavpur University CMATER Lab May 2025 – September 2025

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.

Projects

TailorCV.ai

Python, FastAPI, LLM, AI agents, Amazon Web Services

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 it, and deployed on AWS ECS.
Achieved over 50 users within the first week of launch, demonstrating strong early adoption and real-world impact.

YouTube Sentiment Analysis

TensorFlow, NLP, AWS EC2, Scikit-learn

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.

Smart Product Pricing

Keras, Hugging Face Transformers, ResNet50, OpenCV

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.

Education

Bachelor of Technology — Jadavpur University, Kolkata Nov 2023 – Dec 2027

Higher Secondary — Hariyana Vidya Mandir, Kolkata Apr 2020 – Apr 2022

Activities & 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).

Contact: shubhamsarkarthe1@gmail.com

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