Kantajit Shaw

Senior Applied Machine Learning & Deep Learning Engineer
Machine learning engineer with 9 years of experience building production ML systems across deep learning, NLP, and computer vision. Specialized in designing and deploying large-scale ML infrastructure, LLM-assisted intelligent systems, and end-to-end model lifecycle management for mission-critical applications.
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Experience

Zenon 2022 – Present
Senior Applied Machine Learning Engineer
  • Designed and deployed entity resolution system using deep learning embeddings and graph-based matching, processing millions of records with sub-second latency in production
  • Built document intelligence pipeline combining vision transformers and LLMs for structured data extraction from complex legal and financial documents
  • Developed LLM-assisted code intelligence platform for legacy codebase analysis, enabling automated refactoring suggestions and dependency mapping across multi-million line repositories
  • Established ML model monitoring infrastructure with automated drift detection and retraining pipelines, reducing model degradation incidents
Barclays 2019 – 2022
Machine Learning Engineer
  • Implemented model monitoring and observability framework for credit risk models, tracking performance metrics and data quality across production environments
  • Built scalable data pipelines using Python and SQL for feature engineering and model serving, processing terabytes of transactional data daily
  • Collaborated with risk and compliance teams to establish ML model governance practices, ensuring regulatory alignment and auditability
  • Improved model deployment reliability through containerization and automated testing, reducing deployment time and production incidents
Voxomos Systems 2016 – 2019
Computer Vision Engineer
  • Developed end-to-end OCR system using convolutional neural networks for multi-language document digitization, deployed across enterprise clients
  • Designed and trained custom deep learning architectures for object detection and classification in industrial inspection applications
  • Improved model accuracy through systematic data augmentation strategies and architecture optimization, achieving production-grade performance on challenging real-world datasets
  • Owned complete ML lifecycle from data collection and annotation to model training, evaluation, and production deployment

Skills

Applied ML & Deep Learning

Model architecture design, training optimization, transfer learning, feature engineering, ensemble methods, model evaluation

GenAI & LLMs

Prompt engineering, RAG systems, fine-tuning, embedding models, LLM orchestration, semantic search

Computer Vision & NLP

CNNs, transformers, object detection, OCR, text classification, named entity recognition, sequence modeling

Programming & Systems

Python, SQL, PyTorch, TensorFlow, scikit-learn, pandas, NumPy, Docker, Git, REST APIs

ML Infrastructure

Model deployment, monitoring, versioning, A/B testing, feature stores, pipeline orchestration, MLOps practices

Cloud & Data Platforms

AWS, GCP, Azure, Kubernetes, Spark, Airflow, PostgreSQL, Redis, vector databases

Education

Post Graduate Diploma in AI & ML

IIITB (2021 - 2022)

Master of Science (M.Sc.), Computer Science

Ramakrishna Mission Vivekananda Educational and Research Institute (2014 - 2016)

Bachelor of Science (B.Sc.), Computer Science

Ramakrishna Mission Vidyamandira (2011 - 2014)