Available to hire
Hi, I’m Shravani Kuragayala, an AI/ML Engineer with 3 years of experience building and deploying data-driven solutions in enterprise environments. I design, train, and deploy ML models, fine-tune deep neural networks, and integrate LLMs into production systems using Python, PyTorch, TensorFlow, and AWS.
I thrive on improving model accuracy, reducing latency, and strengthening retriever/QA pipelines through Generative AI and modern MLOps practices. I enjoy collaborating across teams to deliver scalable, reliable AI solutions.
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Language
English
Fluent
Work Experience
AI/ML Engineer at Adobe
February 1, 2024 - PresentDeveloped a retrieval-augmented generation (RAG) pipeline combining transformer models and Pinecone to improve document retrieval accuracy by 37% across enterprise knowledge platforms. Optimized LLMs on AWS SageMaker via quantization and pruning, reducing inference latency by 28% while preserving contextual performance. Built automated evaluation framework for generative summarization, boosting benchmark accuracy by 22% with custom metrics and continuous feedback. Led end-to-end migration of ML models to containerized microservices, reducing production downtime by 40% and saving 48 engineering hours. Integrated FAISS and LangChain to speed retrieval by 31% with more precise contextual enterprise query results. Established centralized logging and alerting via ELK stack, cutting MTTR by 4 hours and preventing production downtime.
Associate AI/ML Engineer at Persistent Systems
August 1, 2023 - October 3, 2025Designed gradient boosting classification pipeline improving churn prediction by 33%. Engineered CNN-based medical imaging pipeline boosting diagnostic precision by 29% and reducing false positives by 12%. Implemented data preprocessing framework for tabular datasets, reducing manual cleaning workload by 41%. Built LSTM forecasting model for retail sales with 25% improved accuracy. Deployed FastAPI microservices with Docker, improving API responsiveness by 32%. Automated experiment tracking using MLflow, cutting duplicated training runs by 36% and improving reproducibility across teams.
AI/ML Engineer at Adobe
February 1, 2024 - PresentImplemented a retrieval-augmented generation (RAG) pipeline by combining transformer models and Pinecone, improving document retrieval accuracy by 37% across enterprise-scale knowledge management platforms. Optimized LLMs via quantization and pruning on AWS SageMaker, reducing inference latency by 28% while preserving contextual performance. Created an automated evaluation framework for generative summarization models, boosting benchmark accuracy by 22% through custom metrics and continuous feedback loops. Led end-to-end migration of critical ML models to containerized microservices, accelerating issue resolution by 40% and preventing production downtime, saving 48 hours of engineering effort. Integrated FAISS and LangChain within retrieval workflows, delivering 31% faster response times and more precise contextual enterprise query results. Spearheaded centralized logging and alerting infrastructure using the ELK stack, reducing MTTR by 4 hours and averting production downtime.
Associate AI/ML Engineer at Persistent Systems
August 1, 2023 - October 3, 2025Designed a gradient boosting classification pipeline, enhancing churn prediction accuracy by 33% and enabling data-driven retention strategies for client subscription platforms. Engineered a CNN-based medical imaging pipeline, boosting diagnostic precision by 29% and reducing false positives by 12%, aiding cardiac disease detection. Built a robust data preprocessing framework for tabular datasets, reducing manual cleaning workload by 41% and ensuring training data reliability across projects. Constructed an LSTM forecasting model for retail sales, improving demand accuracy by 25% and strengthening inventory optimization. Deployed FastAPI microservices with Docker, improving API responsiveness by 32% under heavy client workloads. Automated experiment tracking using MLflow, reducing duplicated training runs by 36% and improving long-term reproducibility across distributed teams.
AI/ML Engineer at Adobe
February 1, 2024 - PresentLed end-to-end MLOps initiatives, including building a RAG pipeline with transformer models and Pinecone to boost enterprise document retrieval accuracy by 37%. Optimized LLMs using quantization and pruning on AWS SageMaker to reduce inference latency by 28% while preserving performance. Created an automated evaluation framework for generative summarization models, achieving a 22% benchmark accuracy improvement. Migrated critical models to containerized microservices, accelerating issue resolution by 40% and reducing downtime. Integrated FAISS and LangChain into retrieval workflows for faster, more accurate contextual results. Established ELK-based logging and alerting to reduce MTTR by 4 hours and prevent production downtime.
Associate AI/ML Engineer at Persistent Systems
August 1, 2023 - October 3, 2025Designed gradient boosting churn classifier improving churn prediction by 33%; engineered CNN-based medical imaging pipeline boosting diagnostic precision by 29% and reducing false positives by 12%; built automated data preprocessing framework for tabular datasets reducing manual cleaning by 41%; developed LSTM forecasting for retail sales improving demand accuracy by 25%; deployed FastAPI microservices with Docker to improve API responsiveness by 32%; automated experiment tracking with MLflow reducing duplicated training runs by 36% and improving reproducibility.
AI/ML Engineer at Adobe
February 1, 2024 - PresentDeveloped a retrieval-augmented generation (RAG) pipeline by integrating transformer models with Pinecone, boosting document retrieval accuracy by 37% across enterprise knowledge management platforms. Optimized LLMs on AWS SageMaker via quantization and pruning to reduce inference latency by 28% while preserving contextual performance. Created an automated evaluation framework for generative summarization models, achieving a 22% improvement in benchmark accuracy through custom metrics and continuous feedback. Led end-to-end migration of critical ML models to containerized microservices, accelerating issue resolution by 40% and reducing production downtime. Integrated FAISS and LangChain to streamline retrieval workflows, delivering 31% faster response times with more precise context. Implemented centralized logging and alerting using the ELK stack, reducing mean time to resolution by 4 hours and preventing downtime.
Associate AI/ML Engineer at Persistent Systems
August 1, 2023 - October 3, 2025Designed gradient boosting classification pipeline enhancing churn prediction by 33%, enabling data-driven retention strategies for client subscriptions. Engineered a CNN-based medical imaging pipeline that improved diagnostic precision by 29% and reduced false positives by 12%, aiding cardiac disease detection. Implemented a data preprocessing framework for tabular datasets, reducing manual cleaning by 41% and ensuring reliable training data. Built an LSTM-based retail sales forecasting model, improving demand accuracy by 25% and supporting inventory optimization. Deployed FastAPI microservices with Docker, achieving 32% better API responsiveness under heavy client loads. Automated experiment tracking with MLflow, cutting duplicated training runs by 36% and improving reproducibility across distributed teams.
AI/ML Engineer at Adobe
February 1, 2024 - November 18, 2025Developed a retrieval-augmented generation (RAG) pipeline by combining transformer models and Pinecone, improving document retrieval accuracy by 37% across enterprise-scale knowledge platforms. Optimized large language models with quantization and pruning on AWS SageMaker, reducing inference latency by 28% while maintaining contextual performance. Built an automated evaluation framework for generative summarization models, boosting benchmark accuracy by 22% through custom metrics and continuous feedback. Led end-to-end migration of critical ML models to containerized microservices, accelerating issue resolution by 40% and preventing production downtime. Integrated FAISS and LangChain within retrieval workflows, delivering 31% faster response times with more precise enterprise query results. Established centralized logging and alerting infrastructure with the ELK stack, reducing MTTR by 4 hours and preventing production outages.
Associate AI/ML Engineer at Persistent Systems
August 1, 2023 - August 1, 2023Designed a gradient-boosting classification pipeline that improved churn prediction by 33%, enabling data-driven strategies for client subscriptions. Engineered a CNN-based medical imaging pipeline that increased diagnostic precision by 29% and reduced false positives by 12%, supporting better healthcare decisions. Implemented a preprocessing framework for tabular data that cut manual cleaning by 41%, ensuring reliable training data. Built an LSTM-based retail sales forecast model that raised demand accuracy by 25% and supported inventory optimization. Deployed FastAPI microservices with Docker to boost API responsiveness by 32% under heavy load. Automated experiment tracking with MLflow, reducing duplicated runs by 36% and improving reproducibility across teams.
Associate AI/ML Engineer at Persistent Systems
January 1, 2022 - August 1, 2023Designed gradient boosting classification pipeline, enhancing churn prediction accuracy by 33%, empowering data-driven strategies within client subscription platforms. Engineered a CNN-based medical imaging pipeline, boosting diagnostic precision by 29% and reducing false positives by 12% for cardiac disease detection. Programmed data preprocessing framework for tabular datasets, reducing manual cleaning workload by 41% and ensuring reliable training data across projects. Constructed LSTM forecasting model for retail sales prediction, improving demand accuracy by 25%. Deployed FastAPI microservices with Docker, improving API responsiveness by 32% under heavy client workloads. Automated experiment tracking using MLflow, cutting duplicated training runs by 36% and enhancing long-term reproducibility across distributed teams.
Education
Master of Science in Advanced Data Analytics at University of North Texas – Denton, TX, USA
August 1, 2023 - December 1, 2024Bachelor of Technology in Computer Science and Engineering at G. Narayanamma Institute of Technology and Science – Hyderabad, India
August 1, 2019 - April 1, 2023Master of Science in Advanced Data Analytics at University of North Texas – Denton, TX, USA
August 1, 2023 - December 1, 2024Bachelor of Technology in Computer Science and Engineering at G. Narayanamma Institute of Technology and Science – Hyderabad, India
August 1, 2019 - April 1, 2023Master of Science in Advanced Data Analytics at University of North Texas – Denton, TX, USA
August 1, 2023 - December 1, 2024Bachelor of Technology in Computer Science and Engineering at G. Narayanamma Institute of Technology and Science – Hyderabad, India
August 1, 2019 - April 1, 2023Master of Science in Advanced Data Analytics at University of North Texas – Denton, TX, USA
August 1, 2023 - December 1, 2024Bachelor of Technology in Computer Science and Engineering at G. Narayanamma Institute of Technology and Science – Hyderabad, India
August 1, 2019 - April 1, 2023Master of Science in Advanced Data Analytics at University of North Texas – Denton, TX, USA
August 1, 2023 - December 1, 2024Bachelor of Technology in Computer Science and Engineering at G. Narayanamma Institute of Technology and Science – Hyderabad, India
August 1, 2019 - April 1, 2023Master of Science in Advanced Data Analytics at University of North Texas – Denton, TX, USA
August 1, 2023 - December 1, 2024Bachelor of Technology in Computer Science and Engineering at G. Narayanamma Institute of Technology and Science – Hyderabad, India
August 1, 2019 - April 1, 2023Qualifications
AWS Certified Machine Learning – Specialty
January 11, 2030 - October 3, 2025TensorFlow Developer Certificate (Google)
January 11, 2030 - October 3, 2025Generative AI with Large Language Models – DeepLearning.AI & AWS (Coursera)
January 11, 2030 - October 3, 2025AWS Certified Machine Learning – Specialty
January 11, 2030 - October 3, 2025TensorFlow Developer Certificate (Google)
January 11, 2030 - October 3, 2025Generative AI with Large Language Models – DeepLearning.AI & AWS (Coursera)
January 11, 2030 - October 3, 2025AWS Certified Machine Learning – Specialty
January 11, 2030 - October 3, 2025TensorFlow Developer Certificate
January 11, 2030 - October 3, 2025Generative AI with Large Language Models – DeepLearning.AI & AWS
January 11, 2030 - October 3, 2025AWS Certified Machine Learning – Specialty
January 11, 2030 - October 3, 2025TensorFlow Developer Certificate
January 11, 2030 - October 3, 2025Generative AI with Large Language Models – DeepLearning.AI & AWS
January 11, 2030 - October 3, 2025AWS Certified Machine Learning – Specialty
January 11, 2030 - November 18, 2025TensorFlow Developer Certificate (Google)
January 11, 2030 - November 18, 2025Generative AI with Large Language Models – DeepLearning.AI & AWS (Coursera)
January 11, 2030 - November 18, 2025AWS Certified Machine Learning – Specialty
January 11, 2030 - December 1, 2025TensorFlow Developer Certificate (Google)
January 11, 2030 - December 1, 2025Generative AI with Large Language Models – DeepLearning.AI & AWS (Coursera)
January 11, 2030 - December 1, 2025Industry Experience
Software & Internet, Professional Services, Media & Entertainment, Healthcare, Education
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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