Mounika Ruthala
Atlanta,GA
Summary
SUMMARY :
Dynamic AI/ML Engineer with expertise in deploying Large Language Models (LLMs) like GPT-3.5 and GPT-4, specializing in NLP, data embeddings, and prompt engineering using Azure OpenAI and Amazon SageMaker. Skilled in designing and implementing MLOps pipelines with Kubernetes, GCP, and Jenkins, optimizing machine learning workflows. Proficient in deep learning frameworks like TensorFlow and PyTorch, focusing on sentiment analysis, regression, and classification models. Experienced in Retrieval-Augmented Generation (RAG) using Langchain, A/B testing, and feature engineering for scalable AI solutions, driving business insights through advanced analytics and data engineering.
Overview
10
10
years of professional experience
1
1
Certification
Work History
GEN AI ENGINNER
Delta Air Lines
Atlanta, GA
01.2022 - Current
- Developed and deployed AI-powered chatbots using GPT-3.5, GPT-4, and OpenAI APIs to automate customer service, enhance booking experiences, and provide real-time flight status updates, integrated seamlessly with GCP services
- Designed and optimized Retrieval-Augmented Generation (RAG) pipelines for personalized customer support using vector databases, such as Pinecone, to enhance the chatbot's ability to retrieve relevant flight and booking information
- Built NLP models with TensorFlow and PyTorch to perform sentiment analysis on customer feedback and social media data, providing insights into customer satisfaction and improving service quality
- Leveraged prompt engineering techniques to fine-tune GPT models, creating dynamic prompt templates for diverse use cases, including personalized flight recommendations, automated rebooking, and disruption management
- Implemented scalable AI infrastructure on GCP and Kubernetes, orchestrating model deployment and ensuring high availability of Gen AI services, integrating with GCS buckets for data storage and Amazon SageMaker for model management
- Developed conversational AI solutions with Gemini, enhancing the airline's customer engagement by providing accurate, context-aware responses for flight inquiries, baggage claims, and loyalty program management
- Automated model training and deployment workflows using Apache Airflow and GCP, ensuring efficient model versioning and continuous delivery of AI-driven services while monitoring model performance and feedback loops to ensure optimal responses
Machine Learning Engineer
Bank of America
Indian Land, SC
08.2017 - 12.2021
- Developed and deployed machine learning models, including random forests and neural networks, using Python, Scikit-learn, and TensorFlow to predict credit risk, customer churn, and fraud detection, ensuring regulatory compliance and business alignment
- Built and optimized deep learning models with Keras and TensorFlow for customer sentiment analysis and transaction classification, using NLP techniques to process and analyze unstructured text data from customer interactions
- Leveraged Snowflake for efficient data storage and retrieval, implementing large-scale data pipelines with Pandas and NumPy for model training, validation, and performance analysis across structured and unstructured financial data
- Applied A/B testing and model evaluation techniques to compare and optimize machine learning models, ensuring continuous performance improvement and scalability in production environments
- Integrated Tableau to visualize key insights and model results, enabling stakeholders to make data-driven decisions on customer segmentation, loan approval processes, and risk management
- Employed MLOps practices using ML flow to track experiments, manage model versions, and automate the deployment of models in production, ensuring robustness, scalability, and reproducibility of results
- Collaborated with data engineers to design and maintain efficient ETL pipelines, enabling real-time data processing and feature engineering, while continuously monitoring model performance through dashboards and alerts in a production environment
Machine Learning Engineer
BlueOptima
, India
10.2016 - 02.2017
- Implemented machine learning algorithms such as regression, classification, and clustering using Python libraries like Scikit-learn and TensorFlow to address specific business challenges
- Developed and deployed machine learning models using Python and Scikit-learn to analyze large datasets, leveraging SQL for data extraction and transformation to support business insights and decision-making
- Designed and optimized scalable data processing pipelines using Apache Spark and Hadoop, enabling efficient handling of big data and facilitating real-time analytics for operational insights
- Leveraged AWS services, including SageMaker, to streamline the machine learning workflow, from model development and training to deployment and monitoring, ensuring high availability and performance
- Developed RESTful APIs using FastAPI to enable seamless integration of machine learning models into web applications, providing real-time predictions and enhancing user experience
- Employed ensemble learning techniques, such as XGBoost and stacking models, to improve predictive accuracy for key business metrics, optimizing hyperparameters to achieve superior model performance
Python Developer
KPIT Technologies
, India
07.2014 - 10.2016
- Strong understanding of Python syntax, data types, control structures, and functions, allowing for effective problem-solving and coding
- Familiarity with popular Python libraries such as Pandas, NumPy, and Matplotlib for data manipulation and visualization, as well as Flask or Django for web development
- Understanding of OOP principles like classes, objects, inheritance, and polymorphism to create modular and reusable code
- Experience using Git for version control, enabling collaboration and tracking of code changes in projects
- Completed personal or academic projects using Python, such as building web applications, automation scripts, or data analysis tools to demonstrate practical application of skills
- Basic understanding of SQL and experience with integrating Python applications with databases like SQLite or MySQL for data storage and retrieval
- Ability to approach challenges logically and efficiently, using Python to develop algorithms and solutions to various problems
Education
Computer Science -
Andhra University
IndiaSkills
- Python, Machine Learning, keras, pytourch, TensorFlow, NLP, OPEN AI,snowflake
- LLM, linux, mysql, SQL, random forest, snowflake, GCP, Hadoop, Sentiment Analytics, neural networks, azure, AWS, Bigdata, BigQuery
- RAG,REST, Regression Analysis, Computer Skills, Microsoft word, LinuX, Tablaue
- Leadership, Time management, Communication skills, Customer service, MLops, MLflow, Sagemaker
- Agile Methodology,Cloud Computing,Data Preprocessing and Cleaning,Large dataset management
- Gpt 35, GPT 4, chatbot, Kubernetes, Agile Methodology, feature engineering, prompt engineering, Gcs buckets,Software Engineering
- Speech Recognition, Big data technologies,Statistical Analysis,Multitasking Abilities,Microsoft Azure
Certification
AWS certified Machine learning engineer
Timeline
GEN AI ENGINNER
Delta Air Lines
01.2022 - Current
Machine Learning Engineer
Bank of America
08.2017 - 12.2021
Machine Learning Engineer
BlueOptima
10.2016 - 02.2017
Python Developer
KPIT Technologies
07.2014 - 10.2016
Computer Science -
Andhra University
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