SARASWATI RAMINEEDI
Summary
Summary:- Machine learning professional with Software Engineering experience. Accomplished in building, training, and deploying machine learning (ML) and deep learning (DL) models across multiple domains. Expertise in scaling models within distributed networks. Proficient in data analysis, feature engineering, and model building, with a strong focus on creating language models. Skilled in implementing state-of-the-art models using transfer learning techniques.
Overview
9
9
years of professional experience
Work History
Machine Learning Engineer
Nordstrom
Alpharetta, GA
05.2022 - 07.2023
- Use Transformer for text summarization to generate concise and informative product descriptions for vast inventory, enhancing shopping experience for customers, improving SEO for e-commerce platform, and increasing purchase orders by 40% and product view rate by 20%
- Built Transformer model to web scrape and interpret data from social media and other sources, identifying emerging trends, consumer preferences, and market opportunities
- This enabled company to adapt product offerings and marketing strategies based on insights into industry and competitor activities
- Improve search ranking algorithm that can better understand customer query and led to increase in demand and conversion rate
- Deploy and fine tune models with automated end-to-end pipeline infrastructure and AWS on-cloud infra and in house ML platform
- Evaluate and monitor model performance against KPI's and dashboards for analysis to team, stakeholders
- Productionalize models using Terraform deployment, Kubernetes and docker containers & deploy microservices, on ECS clusters.
ML-Senior Software Engineer
AT&T
Alpharetta, GA
01.2021 - 04.2022
- Built recommendation system to predict user behavior and suggest services increased user engagement ,retention by 70%
- Used Bert-based summarization model for extractive summarization on tech install documents
- Developed Transformer model, and fine-tuned it using Pytorch to generate summaries on troubleshooting documents and manuals with an accuracy of 95%
- Designed and developed scalable APIs using FastAPI to get the product as a summary
- Performed offline/online A/B testing to evaluate performance on prod real-time data and used NoSQL DB
- Continuously monitored, retrained, and deployed models on AWS, performed inference and monitored for data drift and targeted business KPI's
ML-Senior Software Engineer
USAA
Austin, TX
11.2019 - 12.2020
- Provided efficient insurance recommendations to customers using efficient recommendation system
- Developed feedback mechanism on top of recommendation system to improve prediction quality by 70%
- Made models production ready and deployed into production using AWS and RESTful APIs
- Built pipelines for efficient experimentation on new data sources, feature engineering, model architectures in AWS cloud
- Led cross-functional project to optimize models targeting KPIs, apply s/w best practices for scalability.
Senior Software Engineer
ML, WellsFargo
Hyderabad
12.2017 - 09.2019
- Improved existing classification model accuracy by retraining based on customer data drifts
- Built and operated highly efficient end-to-end data and Machine Learning systems
- Created ability to identify cyber fraud ,created predictive models as part of ML fraud detection system
- Performed statistical analysis and ML algorithms and techniques for complex problems.
Software Engineer
Infosys, BOFA, HSBC
06.2014 - 11.2017
- Developed application using Java/J2EE technologies
- Used Hibernate, Springboot for persistence and application layers
- Used CI-CD pipelines to deploy code and Jenkins for monitoring
- Involved in writing Multi-Threading Synchronization concepts in Java Programs
- Image Classification
- Performed image classification to detect pneumonia by scanning chest X-rays
- Applied pre-trained DL model ResNet and fine-tuned to achieve 94% accuracy.
Education
Bachelor’s of Technology - Computer Science & Engineering
JNTU Kakinada University Campus
2014
Advanced GenAI, Interview Kickstart Machine Learning Certification, Springboard -
Skills
- Machine learning :
- Logistic/Linear regression, SVM, Random forest, XGboost, KNN
- Deep learning Libraries Languages Frameworks Databases Others
- NLP, LSTM, Encoder-decoder, Transformer, BERT, LLM, GenAI, GAN
- Pandas, Sklearn, Nltk, matplotlib, Numpy
- SpringBoot, Pytorch, Keras, Tensorflow, Scikit-learn
- Python, SQL, Java8
- MySQL, Dynamo DB, Redshift
- AWS Sagemaker/services, S3, Terraform, Bitbucket, Kafka, Cloudformation, Kubernetes, Docker
- Cloudwatch, Kibana, Teamcity, Elasticsearch, Lambda, Airflow, RabbitMQ, microservices
Timeline
Machine Learning Engineer
Nordstrom
05.2022 - 07.2023
ML-Senior Software Engineer
AT&T
01.2021 - 04.2022
ML-Senior Software Engineer
USAA
11.2019 - 12.2020
Senior Software Engineer
ML, WellsFargo
12.2017 - 09.2019
Software Engineer
Infosys, BOFA, HSBC
06.2014 - 11.2017
Bachelor’s of Technology - Computer Science & Engineering
JNTU Kakinada University Campus