
Nilufa Sultana
@nilufasultana
I build Python-based LLM, NLP, and computer vision applications end to end.
What I'm looking for
I've built end-to-end AI applications using Python, Hugging Face models, REST APIs, React, Golang, and SQLite3.
For my Journal App, I integrated mistralai/mixtral models for multilingual sentiment analysis, emotion classification, and AI text generation. I designed prompts, parsed JSON API responses, and created a RAG-style flow to retrieve relevant journal context for generation tasks.
I also trained and deployed a CNN-based real-time face mask detection system using TensorFlow, Keras, and OpenCV. I connected live webcam inference to NoSQL event logging and evaluated performance with precision, recall, F1-score, and confusion matrices.
At Cognizant, I automate validation and reporting workflows with Python, test software behavior, and support cloud applications in a live production environment. I'm eager to contribute to AI/ML teams building LLM, RAG, and AI chatbot-driven solutions.
Experience
Work history, roles, and key accomplishments
Analyst Trainee – Technology & Operations
Dec 2025 - Present (9 months)
Apply analytical and problem-solving skills in a live production environment, automating validation and reporting workflows through Python scripting. Collaborate with cross-functional teams in an Agile environment and administer Azure Active Directory, with exposure to AWS on the LPL Financial project.
Education
Degrees, certifications, and relevant coursework
Acharya Prafulla Chandra College
Bachelor of Science, Computer Science
Grade: 8.83 CGPA
Bachelor of Computer Science with a CGPA of 8.83, including coursework in Artificial Intelligence, Machine Learning, and Data Mining.
Purba Barasat Adarsha Bhidyapeeth HS
Higher Secondary, Science
Grade: 85.20%
Higher Secondary education in Physics, Chemistry, Mathematics, and Biology with a score of 85.20%.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Job categories
Skills
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