G Arun Krishna
ML Engineer
Kochi, IN.About
Highly innovative ML Engineer with 3+ years of expertise in designing and deploying scalable machine learning and Generative AI solutions across Google Cloud Platform (GCP) and AWS. Proven success in architecting production-ready AI systems, including Retrieval-Augmented Generation (RAG) and LLM frameworks, for major financial clients. Adept at leveraging MLOps frameworks to deliver impactful, monitored AI solutions at scale, driving significant improvements in accuracy and efficiency.
Work
Tata Consultancy Services Ltd
|ML Engineer (Client: Lloyds Banking Group PLC)
Kochi, Kerala, India
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Summary
Currently serving as an ML Engineer for Lloyds Banking Group PLC, leading the development and deployment of advanced ML and Generative AI solutions on GCP.
Highlights
Architected a Retrieval Augmented Generation (RAG) system on GCP, leveraging Vertex AI for vector embeddings and LangChain, improving information retrieval accuracy by 40%.
Directed the development of a comprehensive LLM risk assessment framework using GCP Model Garden APIs, decreasing false negatives by 75% in detecting hallucination, toxicity, and bias.
Engineered a credit report summarizer with prompt optimization, processing 200+ PDF reports daily with 85% accuracy via a custom UI and FastAPI backend.
Led the design and deployment of an MLOps pipeline using Vertex AI Pipelines and Kubeflow, reducing ML solution deployment time by 60% through automated A/B testing.
American Express Limited
|ML Engineer (Client Engagement)
Remote, Kerala, India
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Summary
Supported data science initiatives for American Express Limited, focusing on anomaly detection, feature engineering, and model development to enhance fraud detection and customer feedback analysis.
Highlights
Developed an anomaly detection model using Scikit-learn to identify unusual transaction patterns, enhancing fraud detection efforts.
Implemented Python-based feature engineering pipelines, improving financial data ML model performance by 8%.
Evaluated model performance using standard metrics and visualization techniques, identifying key areas for improvement in data science initiatives.
Contributed to the development of a classification model using AutoML on Vertex AI, achieving 75% accuracy in categorizing customer feedback.
Education
Nehru College of Engineering and Research Center
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Bachelor of Technology
Mechanical Engineering
Lakshmi Narayana Vidya Niketan
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Secondary Education
Senior Secondary School
Skills
Machine Learning
Deep Learning, NLP, Computer Vision, Feature Design, Predictive Analytics.
ML Frameworks
TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, LangChain, LangGraph, Model Context Protocol, Agentic AI.
GCP AI/ML
Vertex AI, AutoML, Model Garden, Vector Search, Generative AI Studio.
MLOps & Tools
Kubeflow, MLflow, REST APIs, FastAPI, Python, SQL, Docker, Kubernetes, Git, CI/CD.
Cloud & Data
GCP, AWS, S3, Sagemaker, BigQuery, Cloud Storage, Pub/Sub, Dataflow, Cloud Composer (Airflow).