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I am an AI/ML Engineer with over 4 years of experience in designing, developing, and deploying scalable machine learning and deep learning solutions. I specialize in turning data into actionable insights and robust AI systems that drive business value. I am proficient in Python and SQL, with expertise in scikit-learn, XGBoost, TensorFlow, PyTorch, and Keras for predictive modeling, NLP, and computer vision. I have strong data engineering and deployment experience using Pandas, Spark, Hadoop, Flask, FastAPI, Docker, and Kubernetes, and I follow MLOps practices on AWS SageMaker, MLflow, and CI/CD pipelines. I also enjoy building intuitive visualizations with Tableau and Power BI to support data-driven decisions.…I am an AI/ML Engineer with over 4 years of experience in designing, developing, and deploying scalable machine learning and deep learning solutions. I specialize in turning data into actionable insights and robust AI systems that drive business value. I am proficient in Python and SQL, with expertise in scikit-learn, XGBoost, TensorFlow, PyTorch, and Keras for predictive modeling, NLP, and computer vision. I have strong data engineering and deployment experience using Pandas, Spark, Hadoop, Flask, FastAPI, Docker, and Kubernetes, and I follow MLOps practices on AWS SageMaker, MLflow, and CI/CD pipelines. I also enjoy building intuitive visualizations with Tableau and Power BI to support data-driven decisions.

Nikhil Yenuganti

AI Engineer, Data Scientist, Full Stack Developer, +2

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I am an AI/ML Engineer with over 4 years of experience in designing, developing, and deploying scalable machine learning and deep learning solutions. I specialize in turning data into actionable insights and robust AI systems that drive business value. I am proficient in Python and SQL, with expertise in scikit-learn, XGBoost, TensorFlow, PyTorch, and Keras for predictive modeling, NLP, and computer vision. I have strong data engineering and deployment experience using Pandas, Spark, Hadoop, Flask, FastAPI, Docker, and Kubernetes, and I follow MLOps practices on AWS SageMaker, MLflow, and CI/CD pipelines. I also enjoy building intuitive visualizations with Tableau and Power BI to support data-driven decisions.…I am an AI/ML Engineer with over 4 years of experience in designing, developing, and deploying scalable machine learning and deep learning solutions. I specialize in turning data into actionable insights and robust AI systems that drive business value. I am proficient in Python and SQL, with expertise in scikit-learn, XGBoost, TensorFlow, PyTorch, and Keras for predictive modeling, NLP, and computer vision. I have strong data engineering and deployment experience using Pandas, Spark, Hadoop, Flask, FastAPI, Docker, and Kubernetes, and I follow MLOps practices on AWS SageMaker, MLflow, and CI/CD pipelines. I also enjoy building intuitive visualizations with Tableau and Power BI to support data-driven decisions.

Available to hire

I am an AI/ML Engineer with over 4 years of experience in designing, developing, and deploying scalable machine learning and deep learning solutions. I specialize in turning data into actionable insights and robust AI systems that drive business value.

I am proficient in Python and SQL, with expertise in scikit-learn, XGBoost, TensorFlow, PyTorch, and Keras for predictive modeling, NLP, and computer vision. I have strong data engineering and deployment experience using Pandas, Spark, Hadoop, Flask, FastAPI, Docker, and Kubernetes, and I follow MLOps practices on AWS SageMaker, MLflow, and CI/CD pipelines. I also enjoy building intuitive visualizations with Tableau and Power BI to support data-driven decisions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

AI/ML Engineer at JP Morgan Chase

August 1, 2024 - Present

Implemented ensemble methods and GridSearchCV for hyperparameter tuning, achieving a 15% increase in precision and robustness on transactional datasets. Built deep learning and NLP models using TensorFlow, autoencoders, and NLP libraries to detect anomalies and analyze transaction text, improving fraud detection efficiency by 40%. Created computer vision solutions with OpenCV and YOLO for document verification and image anomaly detection, reducing manual review time by 35%. Processed large-scale datasets with Apache Spark, Hadoop, Pandas, and NumPy, handling 50M+ records daily with optimized ETL pipelines. Deployed scalable ML services using Flask, FastAPI, Docker, AWS, and Kubeflow to enable low-latency inference and 30% faster deployment. Built dashboards in Tableau and Matplotlib for fraud trends and model KPIs to support data-driven decisions. Optimized PostgreSQL/MySQL workflows and conducted A/B tests to enhance real-time scoring.

AI/ML Engineer at Metasystems

June 1, 2020 - July 1, 2023

Developed predictive maintenance models using Scikit-learn, XGBoost, and LightGBM, improving accuracy by 30% and reducing unplanned downtime by 35%. Built deep learning models (LSTM, CNN, RNN, GANs) with Keras and PyTorch for anomaly detection in sensor data, enabling earlier detection of failures by ~25%. Applied NLP to maintenance logs, improving predictive insights by ~20%. Processed large-scale IoT data pipelines via Spark MLlib, Hive, Kafka, Pandas, and SQL. Deployed real-time models with TensorFlow Object Detection API, ONNX, TensorFlow Serving, and Kubernetes for low-latency inference. Built Power BI dashboards for equipment health and KPIs, accelerating operational decisions by 30%. Automated ML workflows with MLflow, DVC, Airflow; deployed on Azure ML and GCP AI Platform, reducing deployment cycles by 25%. Worked in Agile teams delivering production-ready AI/ML solutions.