RAKSHA RAMESH
AI Engineer & Software Development Specialist
AI Engineer and Software Development Specialist with expertise in machine learning, cloud infrastructure, and scalable system design. Currently pursuing Master's in Computer Science with AI concentration at University of Pennsylvania (GPA: 3.88/4.0). Proven track record of delivering high-impact solutions at scale, including reducing system outages by 15% (~$15M savings) at Walmart and achieving 90.78% classification accuracy in published IEEE research. Passionate about leveraging cutting-edge AI technologies to solve complex real-world problems.
Data Science Intern
Crum & Forster
- • Redesigned and migrated Python-based ML pipeline from Serverless Framework to AWS CDK
- • Enabled scalable, event-driven processing of real-time insurance data across cloud-native infrastructure
- • Spearheading ML-driven document extraction using AWS Textract, Bedrock, and Custom Queries
- • Automated structured data capture from unstructured insurance supplements
Software Development Engineer II
Walmart Global Tech
- • Orchestrated bi-weekly Agile/Scrum sprints maintaining 20+ mission-critical microservices
- • Reduced outages by 15% (~$15M savings) implementing rate limiting across five high-traffic microservices
- • Improved system observability and reduced resolution time by 40% with OpenTelemetry integration
- • Ensured high system uptime resolving P0/P1 incidents through cross-functional coordination
Software Development Intern
Walmart Global Tech
- • Drove end-to-end integration of PowerSport Category vehicles, boosting conversion by 10%
- • Increased operational visibility across 5 microservices with Grafana and Splunk dashboards
- • Led testing and deployment of two services with seamless production launches
Teaching Assistant / Product Manager
University of Pennsylvania
- • Defined product strategy for 5 cross-functional student teams guiding MVP development
- • Conducted surveys and usability interviews to synthesize actionable requirements
- • Led weekly stand-ups, managed timelines and budgets, evaluated 20+ product demos
Master of Science in Engineering
University of Pennsylvania
Computer and Information Science • AI Concentration
GPA: 3.88/4.0
Bachelor of Technology
PES University
Computer Science and Engineering • Bangalore, India
Segment Based Abnormality Detection in EEG Recordings
Published in IEEE
- • Achieved 90.78% classification accuracy (surpassing SOTA) using EWT + RFE + Linear SVM
- • Evaluated multiple ML pipelines (EMD, EWT, k-NN, SVM, XGBoost, MLP)
DreamBook - AI-Powered Diary Platform
Personal Project
- • Built AI platform digitizing handwritten, audio, and text entries using Google Cloud APIs
- • Generated consistent character illustrations via fine-tuned Stable Diffusion (DreamBooth + LoRA)
- • Designed Gradio-based interface for personalized comic-style outputs
BART-to-Edge - Real-time Translation Optimization
Research Project
- • Optimized mBART and M2M100 with LoRA and layer freezing for edge devices
- • Cut GPU memory use by 50% and training time by 30%
- • Preserved competitive BLEU scores while maintaining sub-1B model size
ML & Data Science
Cloud & Infrastructure
Programming
DevOps & Observability
IEEE Publication
EEG Abnormality Detection
2022
Graduate Teaching Assistant
University of Pennsylvania
2024 - Present