Anirban Majumder
AI/ML Engineer | Full-Stack Developer
Profile summary
AI/ML engineer specialized in integrating machine learning models into production systems. Expert in building full-stack applications that leverage TensorFlow, scikit-learn, and LLMs for diagnostic and data-driven solutions. Proficient in Python, FastAPI, and cloud technologies (AWS, GCP). Holds three Oracle Cloud Infrastructure certifications in Generative AI, Architecture, and AI Foundations. Experienced in designing data pipelines, automating workflows, and deploying scalable ML-integrated platforms.
Career highlights
Full-Stack Platform Development: Built full-stack diagnostic features using Node.js, Next.js, and Express.js with MongoDB integration, supporting platform scalability and production-ready deployment.
Data Pipeline Automation: Developed automated data extraction pipeline using Selenium and web scraping, reducing manual processing time for recurring business workflows.
Machine Learning Integration: Integrated AI/ML models into diagnostic platform using TensorFlow and scikit-learn, contributing to improved diagnostic accuracy and system reliability.
Cloud & Certification Expertise: Earned three Oracle Cloud Infrastructure certifications: Generative AI Professional, Architect Associate, and AI Foundations Associate (2025).
Key skills
Professional experience
Developed and integrated machine learning models into a full-stack diagnostic platform. Focused on leveraging TensorFlow and scikit-learn to improve diagnostic accuracy while building scalable backend services with Node.js and Express.js.
- Integrated TensorFlow and scikit-learn models into production diagnostic platform, improving prediction accuracy and system reliability.
- Designed and deployed REST APIs using Express.js and Node.js to serve ML model predictions and connect frontend interfaces with MongoDB databases.
- Built full-stack features using Next.js and React.js to visualize ML model outputs and diagnostic results for end users.
- Researched and evaluated ML integration patterns and deployment strategies, documenting architectural recommendations for scaling ML systems.
- Collaborated with data science and backend teams on model optimization, API design, and production deployment workflows.
Built data processing and automation solutions using Python, Django, and web scraping. Designed end-to-end data pipelines to extract, transform, and analyze business data for recruitment workflows.
- Developed automated data extraction pipeline using Selenium and web scraping with Python, reducing manual data processing time by 70% for critical business workflows.
- Built Django-based internal tools with data processing capabilities using Pandas and NumPy to analyze structured datasets and enable data-driven decision-making.
- Implemented end-to-end workflow automation for recurring data tasks, eliminating redundant manual operations and improving team productivity.
- Designed scalable data processing architecture to handle large datasets and complex transformation logic.
Education
Computer Science and Engineering