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I am an AI/ML Engineer with over 4 years of experience designing, developing, and deploying machine learning and generative AI solutions across financial and IT domains. I build end-to-end ML pipelines, fraud detection systems, and LLM-powered applications using Python, TensorFlow, Scikit-Learn, PySpark, and LangChain. I am proficient in cloud platforms (AWS SageMaker, EC2, S3, Redshift, Glue; Azure Data Factory, Synapse), and MLOps tools (Airflow, MLflow, GitHub Actions). I deploy models using Docker and Kubernetes, and I excel at data preprocessing, NLP, time-series modeling, anomaly detection, and cloud-native AI architectures. I collaborate with cross-functional teams to build dashboards in Tableau and Power BI, ensuring actionable insights while adhering to compliance frameworks such as FINRA, HIPAA, and SOX.…I am an AI/ML Engineer with over 4 years of experience designing, developing, and deploying machine learning and generative AI solutions across financial and IT domains. I build end-to-end ML pipelines, fraud detection systems, and LLM-powered applications using Python, TensorFlow, Scikit-Learn, PySpark, and LangChain. I am proficient in cloud platforms (AWS SageMaker, EC2, S3, Redshift, Glue; Azure Data Factory, Synapse), and MLOps tools (Airflow, MLflow, GitHub Actions). I deploy models using Docker and Kubernetes, and I excel at data preprocessing, NLP, time-series modeling, anomaly detection, and cloud-native AI architectures. I collaborate with cross-functional teams to build dashboards in Tableau and Power BI, ensuring actionable insights while adhering to compliance frameworks such as FINRA, HIPAA, and SOX.

Gowthami Chikka

AI Engineer, Full Stack Developer, Cloud Developer, +1

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I am an AI/ML Engineer with over 4 years of experience designing, developing, and deploying machine learning and generative AI solutions across financial and IT domains. I build end-to-end ML pipelines, fraud detection systems, and LLM-powered applications using Python, TensorFlow, Scikit-Learn, PySpark, and LangChain. I am proficient in cloud platforms (AWS SageMaker, EC2, S3, Redshift, Glue; Azure Data Factory, Synapse), and MLOps tools (Airflow, MLflow, GitHub Actions). I deploy models using Docker and Kubernetes, and I excel at data preprocessing, NLP, time-series modeling, anomaly detection, and cloud-native AI architectures. I collaborate with cross-functional teams to build dashboards in Tableau and Power BI, ensuring actionable insights while adhering to compliance frameworks such as FINRA, HIPAA, and SOX.…I am an AI/ML Engineer with over 4 years of experience designing, developing, and deploying machine learning and generative AI solutions across financial and IT domains. I build end-to-end ML pipelines, fraud detection systems, and LLM-powered applications using Python, TensorFlow, Scikit-Learn, PySpark, and LangChain. I am proficient in cloud platforms (AWS SageMaker, EC2, S3, Redshift, Glue; Azure Data Factory, Synapse), and MLOps tools (Airflow, MLflow, GitHub Actions). I deploy models using Docker and Kubernetes, and I excel at data preprocessing, NLP, time-series modeling, anomaly detection, and cloud-native AI architectures. I collaborate with cross-functional teams to build dashboards in Tableau and Power BI, ensuring actionable insights while adhering to compliance frameworks such as FINRA, HIPAA, and SOX.

Available to hire

I am an AI/ML Engineer with over 4 years of experience designing, developing, and deploying machine learning and generative AI solutions across financial and IT domains. I build end-to-end ML pipelines, fraud detection systems, and LLM-powered applications using Python, TensorFlow, Scikit-Learn, PySpark, and LangChain.

I am proficient in cloud platforms (AWS SageMaker, EC2, S3, Redshift, Glue; Azure Data Factory, Synapse), and MLOps tools (Airflow, MLflow, GitHub Actions). I deploy models using Docker and Kubernetes, and I excel at data preprocessing, NLP, time-series modeling, anomaly detection, and cloud-native AI architectures. I collaborate with cross-functional teams to build dashboards in Tableau and Power BI, ensuring actionable insights while adhering to compliance frameworks such as FINRA, HIPAA, and SOX.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Northern Trust

February 1, 2025 - November 7, 2025

Developed and deployed machine learning models for real-time fraud detection in payment transactions using Python, PySpark, Scikit-learn, and TensorFlow; reduced false positives by 22%. Built data pipelines on AWS (Glue, S3, Redshift) and Apache Airflow to automate ingestion, preprocessing, and transformation of high-volume financial datasets for model training. Implemented anomaly detection algorithms leveraging NLP and time-series modeling to identify irregular trading patterns and suspicious account activities. Integrated models into a microservices architecture using Docker, Kubernetes, and REST APIs for secure and scalable deployment within Northern Trust's financial systems. Collaborated with risk management teams to create dashboards in Tableau and Power BI, enabling executives to monitor fraud KPIs and compliance metrics in alignment with FINRA & SOX regulations.

AI/ML Engineer at Streebo Inc

December 1, 2022 - December 1, 2022

Designed and implemented end-to-end machine learning pipelines to automate customer support ticket classification using Python, Scikit-learn, TensorFlow, and NLP libraries (spaCy, NLTK), improving resolution accuracy by 30%. Developed and deployed text classification and sentiment analysis models on structured/unstructured customer data, leveraging AWS SageMaker, EC2, and S3 for scalable ML operations. Built data preprocessing workflows using Pandas, NumPy, and SQL to clean, normalize, and transform raw logs into structured datasets for model training and analytics. Collaborated with software engineers to integrate ML models into RESTful APIs and microservices (Docker, Kubernetes), ensuring seamless integration with enterprise applications. Implemented hyperparameter tuning and model optimization using GridSearchCV, Random Search, and cross-validation to enhance predictive performance and reduce false positives. Monitored model performance through MLOps pipelines using Airflow, MLflow,

AI/ML Engineer at Streebo Inc

September 1, 2019 - December 1, 2022