Shubham Sarkar — Full Stack Developer

01.

About

I'm Shubham Sarkar, a detail-oriented developer with a passion for machine learning and AI. My expertise spans deep learning, NLP, and computer vision, enabling me to build scalable and impactful solutions. I thrive in collaborative environments, turning complex challenges into innovative applications.

02.

Experience

Jan 2026 – Present

Machine Learning Engineer · Alignerr

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.

May 2025 – September 2025

Deep Learning Research Assistant · Jadavpur University CMATER Lab

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.

03.

Selected work

TailorCV.aiCheck out

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 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 AnalysisCheck out

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.

TensorFlowNLPAWS EC2Scikit-learn

Live Demo GitHub

Smart Product PricingCheck out

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.

KerasHugging Face TransformersResNet50OpenCV

GitHub

RAG SystemCheck out

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

04.

Skills & tools

Machine LearningDeep LearningNatural Language Processing (NLP)Computer VisionLLM Fine TuningRAGTensorFlowPyTorchscikit-learnHugging FacePandasNumPyLangchainFlaskFastAPIAmazon Web Services (AWS)DockerMLflowDVCStreamlitCI/CDPostgreSQLSQLETL PipelinesLinuxVector Databases (Chroma)PythonCJavaScriptHTMLCSSData Structures and Algorithms

05.

Education

Jadavpur University, Kolkata

Bachelor of Technology

Nov 2023 – Dec 2027 · CGPA: 7.5

Hariyana Vidya Mandir, Kolkata

Higher Secondary

Apr 2020 – Apr 2022 · Percentage: 90%

06.

Leadership & activities

May 2024 – Present

Core Member · Entrepreneurship Cell, Jadavpur University

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).

Coordinator · Jadavpur University Finance Club

Led planning and execution of Finspire 2025, a national-level finance event with 1,000+ registrations and 500+ on-ground
attendees, strengthening the club’s national presence.
Delivered high-impact trading and investment courses to 100+ students, improving engagement in financial markets

07.

Get in touch

Have a role or a project in mind? I'd love to hear from you.

shubhamsarkarthe1@gmail.com +91 8240044652