Looking for a job

Parthava naidu Jyotha

@parthavanaidujyotha

Machine Learning Engineer at Expedia Group, improving personalized traveler messaging with LLM-based recommendations and production ML pipelines.

United States

Message

At Expedia Group, I integrate LLM-based recommendation components into personalized traveler messaging, using prompt templates, structured JSON outputs, and MLflow tracking. I also turn traveler booking, trip, and engagement records into production-ready features and batch-scoring pipelines.

At PayPal, I built and evaluated fraud and risk models, fine-tuned open-source LLMs for contact categorization, and designed RAG copilots for policy lookup and dispute analysis. I also developed an MCP server with agentic workflows to automate diagnosis of merchant conversion and authorization-rate drops.

At Tata Consultancy Services, I trained churn-prediction models and built a content-based recommendation engine. In my RecruitEdge ATS project, I created a retrieval-based resume-matching service and tuned its RAG pipeline through grounding checks and retrieval evaluation.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

Expedia Group

Mar 2026 - Present (7 months)

Integrating LLM-based recommendation components with prompt templates and structured JSON outputs. Built feature-engineering and batch-scoring pipelines in Python, Spark, Databricks, and SQL, and reduced manual deployment effort by ~30% using Docker, Git, and Flyte.

Python Spark Databricks SQL Docker Git Flyte Airflow MLFlow LLM RAG Prompt Engineering JSON A B Testing Drift Detection Data Quality Management

AI/ML Engineer

PayPal

Sep 2024 - Mar 2026 (1 year 6 months)

Improved fraud-detection precision by ~27% with XGBoost, LightGBM, and scikit-learn models. Scaled contact categorization to 10M+ contacts/month via fine-tuned LLMs, and built RAG-based copilots with LangChain and FAISS to cut policy-lookup time by ~45%.

Python XGBoost LightGBM scikit learn Hugging Face Lang Chain Faiss fastAPI MCP Agentic Workflows PySpark Snowflake Drift Monitoring Data Quality A B Testing

Machine Learning Engineer

Tata Consultancy Services

Dec 2022 - Dec 2023 (1 year)

Achieved 84% accuracy in customer churn prediction using classification models. Automated preprocessing pipelines and built a content-based recommendation engine that lifted offline relevance by 18% and coverage by 21%.