Machine Learning Engineer

PRAMITHI KONGARA

216-***-**** *****************@*****.***

Summary

Highly skilled and results-driven Machine Learning Engineer with over 5 years of experience in designing, developing, and deploying advanced machine learning models and AI solutions. Proficient in leveraging data science, statistical analysis, and state-of-the-art algorithms to solve complex real-world problems. Demonstrated expertise in Python, R, Java, and Scala for scalable machine learning pipelines. Strong capabilities in data cleaning, preprocessing, and data visualization using frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras. Proven ability to deploy models in production environments using Docker, Kubernetes, and MLOps practices. Experienced in cloud-based solutions with AWS, Google Cloud, and Azure to deliver innovative, data-driven insights and solutions. Skills

Programming Languages: Python, R, Java,

C++, Scala, SQL

ML Frameworks: TensorFlow, PyTorch, Scikit-

learn, Keras, XGBoost

Deep Learning: CNN, RNN, GANs, BERT, GPT-

NLP: spaCy, NLTK, Gensim, Word2Vec

Data Preprocessing: Pandas, NumPy, ScipyBig

Data: Hadoop, Spark, Kafka

Deployment: Docker, Kubernetes, Flask

Cloud Platforms: AWS, Google Cloud, Azure

CI/CD & MLOps: Jenkins, Git, MLflow,

Kubeflow

Data Visualization: Tableau, Power BI,

Matplotlib

Computer Vision: OpenCV, YOLO, ResNet

Data Storage: MySQL, PostgreSQL, MongoDB

Real-Time Processing: Kafka, Flink

Edge AI: TensorFlow Lite, ONNX Runtime

Version Control: Git, GitHub

Data Pipelines: Apache Airflow, AWS Glue

Experience

Machine Learning Engineer 03/2024 to Current

Edward Jones Investments St. Louis, Missouri, USA

Designed and deployed machine learning models for financial planning and investment optimization using TensorFlow and PyTorch.

Developed NLP applications for client feedback analysis and automated financial reporting using BERT and GPT models.

Built real-time data processing systems using Apache Kafka and Flink to enhance market trend monitoring.

Implemented MLOps workflows with Kubernetes and MLflow for scalable model deployment.

Created dynamic data visualizations with Tableau and Power BI for data-driven decision-making. Machine Learning Engineer 11/2022 to 02/2024

Energizer Personal Care St. Louis, Missouri, USA

Enhanced battery performance predictions using optimized machine learning algorithms, improving energy efficiency.

Automated data collection and analysis to improve inventory management and detect e-commerce fraud.

Deployed machine learning models to cloud platforms for scalable analysis and predictive maintenance.

Developed real-time data dashboards for product performance using Tableau and Power BI.

Managed continuous integration and delivery pipelines using Jenkins and Docker. Machine Learning Engineer 01/2021 to 07/2022

Genworth Financial Mumbai, INDIA

Implemented predictive analytics for fraud detection and credit scoring to enhance financial risk management.

Deployed deep learning models to predict customer behavior and optimize financial decisions.

Created automated reporting systems for data-driven insights and decision support.

Leveraged Apache Kafka for real-time transaction monitoring and fraud prevention.

Built data warehousing solutions using Snowflake and Google BigQuery for scalable data analysis. Data Scientist 08/2019 to 12/2020

Machine Learning Engineer Intern - Wind Information AbbVie, Mumbai, INDIA

Developed machine learning models to optimize drug discovery and patient recruitment processes.

Implemented predictive analytics for clinical trial data to improve patient safety and outcomes.

Integrated big data technologies for efficient biological and clinical data analysis.

Deployed real-time analytics solutions using Apache Kafka and Flink.

Built scalable data pipelines with Apache Airflow for consistent data management. Education and Training

Computer And Information Sciences

Western Illinois University USA

Contact this candidate