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I am a Production Machine Learning Engineer with over 3 years of experience building and deploying ML systems in regulated financial services. I’ve shipped fraud detection, credit risk, and multi-agent GenAI solutions at Citibank, collaborating with risk, compliance, and operations teams to translate complex data into practical safeguards and scalable workflows. My strengths span NLP, MLOps, model governance, and low-latency inference on AWS and Azure. I thrive on cross-functional partnerships and turning ambitious ideas into robust, observable production systems.…I am a Production Machine Learning Engineer with over 3 years of experience building and deploying ML systems in regulated financial services. I’ve shipped fraud detection, credit risk, and multi-agent GenAI solutions at Citibank, collaborating with risk, compliance, and operations teams to translate complex data into practical safeguards and scalable workflows. My strengths span NLP, MLOps, model governance, and low-latency inference on AWS and Azure. I thrive on cross-functional partnerships and turning ambitious ideas into robust, observable production systems.

Pushwanth Gunturu

App Developer, Web Developer, Front-End Developer, +2

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I am a Production Machine Learning Engineer with over 3 years of experience building and deploying ML systems in regulated financial services. I’ve shipped fraud detection, credit risk, and multi-agent GenAI solutions at Citibank, collaborating with risk, compliance, and operations teams to translate complex data into practical safeguards and scalable workflows. My strengths span NLP, MLOps, model governance, and low-latency inference on AWS and Azure. I thrive on cross-functional partnerships and turning ambitious ideas into robust, observable production systems.…I am a Production Machine Learning Engineer with over 3 years of experience building and deploying ML systems in regulated financial services. I’ve shipped fraud detection, credit risk, and multi-agent GenAI solutions at Citibank, collaborating with risk, compliance, and operations teams to translate complex data into practical safeguards and scalable workflows. My strengths span NLP, MLOps, model governance, and low-latency inference on AWS and Azure. I thrive on cross-functional partnerships and turning ambitious ideas into robust, observable production systems.

Available to hire

I am a Production Machine Learning Engineer with over 3 years of experience building and deploying ML systems in regulated financial services. I’ve shipped fraud detection, credit risk, and multi-agent GenAI solutions at Citibank, collaborating with risk, compliance, and operations teams to translate complex data into practical safeguards and scalable workflows.

My strengths span NLP, MLOps, model governance, and low-latency inference on AWS and Azure. I thrive on cross-functional partnerships and turning ambitious ideas into robust, observable production systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Machine Learning Engineer at Citibank

January 1, 2025 - Present

Led ML initiatives across fraud detection, credit risk, and GenAI at Citibank, partnering with risk, compliance, and operations. Engineered an XGBoost/LightGBM ensemble with anomaly detection on AWS SageMaker, boosting fraud catch rate from 68% to 85% and reducing false positives by 15% across 5M+ daily transactions. Built feature engineering pipelines and credit risk forecasting models (Python, SQL, PostgreSQL), increasing default prediction accuracy by 18% and aligning with Model Risk Management for SR 11-7 documentation. Developed an NLP-based compliance document review system processing 10K+ documents/day using Hugging Face Transformers with optimized C++ inference on AWS Lambda, delivering ~4x latency improvement over Python baselines. Designed and deployed a multi-agent GenAI ticket triage system (LangGraph, CrewAI, Claude, GPT-4) auto-classifying 3K+ tickets/week with 92% accuracy, reducing resolution time by 35% and saving ~120 analyst-hours/month. Architected a production RAG

Machine Learning Engineer at Techcore

January 1, 2022 - December 1, 2023

Owned production reliability and MLOps for 12+ ML models (NLP, computer vision, and recommendations) on Azure ML/AKS, maintaining 99.9% uptime through automated health checks, canary deployments, Kubeflow pipelines, and drift detection with Prometheus/Grafana. Boosted click-through rates by 25% and drove $500K+ incremental quarterly revenue by fine-tuning CNN and Transformer models (PyTorch, TensorFlow) for e-commerce product recommendations. Built a real-time recommendation engine using Azure Cognitive Search, MongoDB, and Redis, reducing p95 latency to 100 ms. Reduced inference latency from 250 ms to under 100 ms using ONNX/TensorRT on Azure GPU clusters for latency-sensitive ad ranking.