Open to opportunities

Elaina Hill

@elainahill

Message

Full-stack engineer building secure AWS platforms and production-ready ML workflows.

United States

Message

What I'm looking for

I want to architect intelligent, reliable systems that accelerate research and operational insights—building secure, scalable full-stack platforms and integrating production-ready ML into real-time workflows in an Agile team.

I’m a Full Stack Engineer with 4+ years building full-stack web platforms and production-ready ML solutions, supported by a strong background in technical writing and documentation. I combine TypeScript/React frontends with serverless AWS backends to deliver scalable, secure systems and real-time data workflows.

At CyberAssure, I designed and developed a corporate package management platform using Vite/React/TypeScript, Tailwind, and Radix UI, deployed globally via S3 + CloudFront, and managed end-to-end releases with IaC pipelines in AWS CloudFormation. I built backend services with Express/Node.js on AWS Lambda and API Gateway, exposing GraphQL through AWS AppSync backed by DynamoDB streams, while enforcing secure cross-origin communication and smooth REST API integration.

I’ve also engineered multi-role workflows with JWT authentication, per-step form persistence, and pre-signed S3 upload/download flows—reducing manual exchanges and improving operational throughput. My work extends to ML: I developed unsupervised clustering for solar wind data using KMeans/Scikit-learn (with Librosa, NumPy/Pandas, and Matplotlib), and built a CNN-based speech emotion recognition system with Librosa, TensorFlow/Keras, MFCCs/spectrograms, and clear performance evaluation—then translated complex workflows into accessible technical tutorials for diverse audiences.

Experience

Work history, roles, and key accomplishments

Current

Full Stack Engineer

Current

CyberAssure

May 2022 - Present (4 years 1 month)

Designed and developed a corporate package management platform using React, TypeScript, Tailwind, and Radix UI, deploying via S3 and CloudFront with repeatable AWS CloudFormation releases. Built serverless backend services with Express, Lambda, API Gateway, and a GraphQL layer on AppSync with DynamoDB streams, implementing JWT-authenticated multi-role workflows and secure S3 pre-signed upload/down

TypeScript React AWS Lambda API Gateway AWS AppSync DynamoDB AWS CloudFormation Amazon S3 JWT

Software Engineering Intern

NASA – Heliophysics Division

Developed an unsupervised AI model using KMeans to classify solar wind data by preprocessing time-series and spectral features. Applied Librosa and NumPy/Pandas for signal analysis and created Matplotlib visualizations, collaborating with researchers to integrate results into heliophysics pipelines and author technical documentation.

K Means scikit learn Librosa NumPy Pandas data preprocessing Matplotlib Data Visualization

Machine Learning Intern

AI4ALL @ University of Maryland

Built a supervised speech emotion recognition model using convolutional neural networks for vocal emotion detection. Extracted spectral features and MFCCs with Librosa, trained a CNN in TensorFlow/Keras, evaluated performance using confusion matrices, and presented findings to the University of Maryland academic community while translating research into accessible documentation.

Librosa TensorFlow Keras Convolutional Neural Networks (CNNs)MFCC Feature Extraction Spectrogram Visualization Model Training

Education

Degrees, certifications, and relevant coursework

University of Maryland

Bachelor of Science, Computer Science

Grade: 4.0/4.0 GPA

Activities and societies: President’s List (Summer 2025); Dean’s List (Spring 2025, Summer 2025); Phi Theta Kappa (2022); NCWIT Honorable Mention (2022); Summa cum laude (2025).

Completed a Bachelor of Science in Computer Science at the University of Maryland. Earned a 4.0/4.0 GPA and graduated with honors.