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I am a Machine Learning Engineer with 4+ years of experience building and deploying end-to-end AI/ML solutions. I specialize in Python, TensorFlow, PyTorch, and NLP frameworks like BERT, GPT, and Llama. I work across cloud platforms (AWS, GCP, Azure), big data tools (Spark, Kafka), and MLOps practices (Docker, MLflow, CI/CD). I have delivered production-ready models for automation, prediction, and intelligent decision-making. Highlights include forecasting insurance claims with XGBoost and SHAP, extracting insights from unstructured medical documents with BERT and spaCy, real-time fraud detection, explainable AI frameworks, and fairness-focused modeling developed with cross-functional teams. I have led migration of training workflows to AWS SageMaker and built reproducible ML pipelines, dashboards, and governance for regulatory approval.…I am a Machine Learning Engineer with 4+ years of experience building and deploying end-to-end AI/ML solutions. I specialize in Python, TensorFlow, PyTorch, and NLP frameworks like BERT, GPT, and Llama. I work across cloud platforms (AWS, GCP, Azure), big data tools (Spark, Kafka), and MLOps practices (Docker, MLflow, CI/CD). I have delivered production-ready models for automation, prediction, and intelligent decision-making. Highlights include forecasting insurance claims with XGBoost and SHAP, extracting insights from unstructured medical documents with BERT and spaCy, real-time fraud detection, explainable AI frameworks, and fairness-focused modeling developed with cross-functional teams. I have led migration of training workflows to AWS SageMaker and built reproducible ML pipelines, dashboards, and governance for regulatory approval.

Kotesh Kumar Yelamati

Data Scientist, AI Engineer, AI Developer, +2

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I am a Machine Learning Engineer with 4+ years of experience building and deploying end-to-end AI/ML solutions. I specialize in Python, TensorFlow, PyTorch, and NLP frameworks like BERT, GPT, and Llama. I work across cloud platforms (AWS, GCP, Azure), big data tools (Spark, Kafka), and MLOps practices (Docker, MLflow, CI/CD). I have delivered production-ready models for automation, prediction, and intelligent decision-making. Highlights include forecasting insurance claims with XGBoost and SHAP, extracting insights from unstructured medical documents with BERT and spaCy, real-time fraud detection, explainable AI frameworks, and fairness-focused modeling developed with cross-functional teams. I have led migration of training workflows to AWS SageMaker and built reproducible ML pipelines, dashboards, and governance for regulatory approval.…I am a Machine Learning Engineer with 4+ years of experience building and deploying end-to-end AI/ML solutions. I specialize in Python, TensorFlow, PyTorch, and NLP frameworks like BERT, GPT, and Llama. I work across cloud platforms (AWS, GCP, Azure), big data tools (Spark, Kafka), and MLOps practices (Docker, MLflow, CI/CD). I have delivered production-ready models for automation, prediction, and intelligent decision-making. Highlights include forecasting insurance claims with XGBoost and SHAP, extracting insights from unstructured medical documents with BERT and spaCy, real-time fraud detection, explainable AI frameworks, and fairness-focused modeling developed with cross-functional teams. I have led migration of training workflows to AWS SageMaker and built reproducible ML pipelines, dashboards, and governance for regulatory approval.

Available to hire

I am a Machine Learning Engineer with 4+ years of experience building and deploying end-to-end AI/ML solutions. I specialize in Python, TensorFlow, PyTorch, and NLP frameworks like BERT, GPT, and Llama. I work across cloud platforms (AWS, GCP, Azure), big data tools (Spark, Kafka), and MLOps practices (Docker, MLflow, CI/CD).

I have delivered production-ready models for automation, prediction, and intelligent decision-making. Highlights include forecasting insurance claims with XGBoost and SHAP, extracting insights from unstructured medical documents with BERT and spaCy, real-time fraud detection, explainable AI frameworks, and fairness-focused modeling developed with cross-functional teams. I have led migration of training workflows to AWS SageMaker and built reproducible ML pipelines, dashboards, and governance for regulatory approval.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Machine Learning Engineer at Genworth

October 1, 2024 - Present

Coordinated cross-functional teams to plan and execute machine learning projects under Agile methodology, conducting sprint planning and retrospectives to boost delivery efficiency by 10%. Designed and deployed a predictive risk assessment model using XGBoost and SHAP to forecast long-term care insurance claims, improving early risk detection by 28% and reducing false positives by 15%. Built an NLP pipeline with BERT and spaCy to extract insights from unstructured medical documents and underwriting notes, leading to 20% faster claims review by automating feature extraction. Integrated a real-time fraud detection system using Isolation Forest and Autoencoder models, identifying anomalous claim patterns and reducing fraudulent payouts by $2M annually. Led the migration of model training workflows to AWS SageMaker, implementing CI/CD with AWS Code Pipeline and reducing deployment time from days to hours. Developed an Explainable AI (XAI) framework for underwriters using LIME and SHAP, enh

AI/ML Engineer at Infinite Infolab

April 1, 2020 - July 1, 2023

Developed computer vision-based defect detection system using YOLOv5 and OpenCV for a manufacturing client, achieving 94% accuracy in real-time anomaly detection on the assembly line. Built a multilingual chatbot using Rasa and spaCy, integrated with client CRM via REST APIs, reducing support tickets by 35% across English, Hindi, and Tamil users. Led an AI-driven customer churn prediction project using LightGBM and survival analysis, improving retention strategies and reducing churn by 22% for an e-commerce client. Designed and deployed a recommendation engine using Collaborative Filtering and Matrix Factorization for a retail client, increasing cross-sell revenue by 18%. Created time-series forecasting models with ARIMA, Prophet, and LSTM to predict energy demand for a smart-grid solution, achieving MAPE < 7% on unseen data. Developed and productionized ML pipelines using MLflow, Airflow, and Docker, ensuring reproducibility and reducing experimentation time by 40%. Conducted end-to-e

AI/ML Engineer at Infinite Infolab, India

April 1, 2020 - July 1, 2023

Developed a computer vision defect detection system using YOLOv5 and OpenCV for a manufacturing client, achieving 94% accuracy in real-time anomaly detection on the assembly line. Built a multilingual chatbot using Rasa and spaCy, integrated with client CRM via REST APIs, reducing support tickets by 35% across English, Hindi, and Tamil users. Led an AI-driven customer churn prediction project using LightGBM and survival analysis, reducing churn by 22% for an e-commerce client. Designed and deployed a recommendation engine using Collaborative Filtering and Matrix Factorization, increasing cross-sell revenue by 18%. Created time-series forecasting models with ARIMA, Prophet, and LSTM to predict energy demand for a smart-grid solution, achieving MAPE < 7% on unseen data. Developed and productionized ML pipelines using MLflow, Airflow, and Docker, ensuring reproducibility and reducing experimentation time by 40%. Conducted end-to-end model validation and A/B testing, presenting actionable