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Hi, I'm Aishwarya Kobbaji, a data-driven AI/ML Engineer based in Texas, USA, with 3+ years of hands-on experience building production-grade ML and Generative AI solutions. I specialize in end-to-end ML pipelines, feature engineering, model optimization, and deploying scalable RESTful APIs. I'm proficient in Python, SQL, PyTorch, Scikit-learn, XGBoost, TensorFlow, Docker, Kubernetes, and AWS, and I have hands-on experience with MLflow for experiment tracking, automated retraining, and A/B testing. I've led initiatives to develop Generative AI-powered member support and chat solutions using Hugging Face Transformers and OpenAI APIs, achieving improved accuracy and faster responses. I've delivered low-latency inference on AWS with FastAPI, Docker, and Kubernetes, and I'm comfortable working in Agile teams with compliance and security requirements.…Hi, I'm Aishwarya Kobbaji, a data-driven AI/ML Engineer based in Texas, USA, with 3+ years of hands-on experience building production-grade ML and Generative AI solutions. I specialize in end-to-end ML pipelines, feature engineering, model optimization, and deploying scalable RESTful APIs. I'm proficient in Python, SQL, PyTorch, Scikit-learn, XGBoost, TensorFlow, Docker, Kubernetes, and AWS, and I have hands-on experience with MLflow for experiment tracking, automated retraining, and A/B testing. I've led initiatives to develop Generative AI-powered member support and chat solutions using Hugging Face Transformers and OpenAI APIs, achieving improved accuracy and faster responses. I've delivered low-latency inference on AWS with FastAPI, Docker, and Kubernetes, and I'm comfortable working in Agile teams with compliance and security requirements.

Aishwarya Kobbaji

Data Scientist, AI Engineer, AI Developer, +3

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Hi, I'm Aishwarya Kobbaji, a data-driven AI/ML Engineer based in Texas, USA, with 3+ years of hands-on experience building production-grade ML and Generative AI solutions. I specialize in end-to-end ML pipelines, feature engineering, model optimization, and deploying scalable RESTful APIs. I'm proficient in Python, SQL, PyTorch, Scikit-learn, XGBoost, TensorFlow, Docker, Kubernetes, and AWS, and I have hands-on experience with MLflow for experiment tracking, automated retraining, and A/B testing. I've led initiatives to develop Generative AI-powered member support and chat solutions using Hugging Face Transformers and OpenAI APIs, achieving improved accuracy and faster responses. I've delivered low-latency inference on AWS with FastAPI, Docker, and Kubernetes, and I'm comfortable working in Agile teams with compliance and security requirements.…Hi, I'm Aishwarya Kobbaji, a data-driven AI/ML Engineer based in Texas, USA, with 3+ years of hands-on experience building production-grade ML and Generative AI solutions. I specialize in end-to-end ML pipelines, feature engineering, model optimization, and deploying scalable RESTful APIs. I'm proficient in Python, SQL, PyTorch, Scikit-learn, XGBoost, TensorFlow, Docker, Kubernetes, and AWS, and I have hands-on experience with MLflow for experiment tracking, automated retraining, and A/B testing. I've led initiatives to develop Generative AI-powered member support and chat solutions using Hugging Face Transformers and OpenAI APIs, achieving improved accuracy and faster responses. I've delivered low-latency inference on AWS with FastAPI, Docker, and Kubernetes, and I'm comfortable working in Agile teams with compliance and security requirements.

Available to hire

Hi, I’m Aishwarya Kobbaji, a data-driven AI/ML Engineer based in Texas, USA, with 3+ years of hands-on experience building production-grade ML and Generative AI solutions. I specialize in end-to-end ML pipelines, feature engineering, model optimization, and deploying scalable RESTful APIs. I’m proficient in Python, SQL, PyTorch, Scikit-learn, XGBoost, TensorFlow, Docker, Kubernetes, and AWS, and I have hands-on experience with MLflow for experiment tracking, automated retraining, and A/B testing.

I’ve led initiatives to develop Generative AI-powered member support and chat solutions using Hugging Face Transformers and OpenAI APIs, achieving improved accuracy and faster responses. I’ve delivered low-latency inference on AWS with FastAPI, Docker, and Kubernetes, and I’m comfortable working in Agile teams with compliance and security requirements.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Cigna Healthcare

June 1, 2025 - Present

Developed and deployed supervised and ensemble ML models to detect anomalous claims patterns, improving fraud detection precision from 91% to 96% while ensuring HIPAA-compliant data handling. Engineered scalable ETL and feature pipelines using Pandas, SQL, and PySpark on PostgreSQL/Redshift. Built Generative AI-powered member support solutions leveraging Hugging Face Transformers and OpenAI APIs, applying structured prompt engineering to improve chatbot resolution accuracy. Designed low-latency REST APIs using FastAPI, Docker, and Kubernetes on AWS, achieving sub-120 ms inference times and 99.95% availability. Implemented MLflow-based experiment tracking and automated retraining workflows, proactively monitoring model performance drift. Collaborated with product owners, compliance teams, and DevOps in Agile Scrum for ethical AI governance and reproducibility.

AI/ML Engineer at Mphasis

September 1, 2022 - November 1, 2023

Constructed end-to-end machine learning pipelines on AWS, integrating data ingestion, feature engineering, training, and deployment; improved fraud detection precision from 88% to 93%, developed and fine-tuned supervised and ensemble models using Scikit-learn and XGBoost; built Generative AI prototypes leveraging Hugging Face Transformers and OpenAI API integration; deployed containerized inference services using Docker and FastAPI on EC2; applied MLflow for experiment tracking; planned scalable data preprocessing with Pandas and SQL on PostgreSQL, improving data quality and model readiness; integrated predictive analytics APIs into enterprise applications, contributing to efficiency gains measured via A/B testing.

ML Engineer at Freshworks

July 1, 2021 - August 1, 2022

Created end-to-end ML pipelines using Python and AWS, integrating ETL, model training, validation, and REST API deployment; improved ticket routing accuracy by 18% across CRM workflows. Developed churn prediction models with Scikit-learn/XGBoost, achieving F1-score improvement from 0.79 to 0.87. Deployed low-latency inference services with FastAPI and Docker on EC2 (sub-180 ms). Used MLflow for experiment tracking and reproducible training workflows; built data preprocessing pipelines with Pandas and SQL to clean high-volume CRM logs, reducing missing label inconsistencies by 30% and improving dataset quality. Collaborated in Agile sprints to embed predictive models into SaaS apps, contributing to a 22% reduction in average support resolution time through A/B testing; monitored production performance and retrained to maintain precision above 90% across evolving datasets.