Harrison Stark

I am a forward-thinking computer science enthusiast deeply committed to innovation and pushing technological boundaries. My passion for continuous learning is evident through hands-on experience and cutting-edge projects. My values extend beyond technology, reflecting a holistic educational background and my relentless pursuit of knowledge.

For information about my hobbies, click here.

Education

Bachelor of Science in Computer Science, Minor in Mathematics - 3.78 GPA (August 2021 - December 2023)
University of Florida

Associate of Arts - 4.0 GPA (January 2019 - May 2021)
Palm Beach State University

High School Diploma - 3.94 GPA (August 2017 - May 2021)
Suncoast Community High School

Experience

Qualtrics - Machine Learning Engineer II (May 2025 - Current)

  • Designed and own the company-wide ML gateway written in Go, serving as the single entry point for all model invocation at Qualtrics. Built for high-throughput concurrent request handling using goroutines, routing vendor-agnostic LLM, embedding, rerank, and self-hosted model traffic across Azure OpenAI, Bedrock, and SageMaker. Handles auth, rate limiting, cost tracking, regional failover, streaming, and caching, serving billions of inferences monthly.
  • Authored and presented a company-wide AI enablement strategy to engineering leadership and executive staff projecting $30M+ annual impact. Secured formal funding and scaled the program from hackathon experiments to an officially funded team, mentoring engineers in delivering the four most-used internal AI tools at the company.
  • Built the Ops Agent as part of the internal AI tooling initiative, winning the company-wide hackathon (People's Choice). An MCP-powered incident triage agent that pulls context from Jira, Slack, GitLab, Splunk, and Google Drive to surface similar tickets, relevant code paths, Kubernetes commands, and Splunk queries, and autofills client response emails. Projects millions in annual savings and is one of the most used internal AI tools at the company.
  • Built and standardized a unified embedding platform with company-wide adoption. Designed the abstraction layer, batching system, and cross-vendor fallback logic. Led integration of self-hosted BGE-M3 (sync and async) to support large-scale semantic search.
  • Authored the design standard for asynchronous ML inference at Qualtrics. Built an SQS + Lambda + Redis pipeline to handle terabyte-scale reindexing workloads, increasing throughput ~10x on the same hardware cost while protecting shared Kubernetes services from saturation.
  • Evaluated agent orchestration frameworks and deployed a self-hosted LangGraph platform as the company standard for agentic development. Replaced an exploratory POC monorepo with production infrastructure, established company-wide patterns for agent architecture, state management, and observability via Galileo, and shipped a retrieval and agent memory system now adopted by 10+ product teams.
  • Leading development of a Context Service that gives LLMs a centralized way to source and build context across the company. POC validated and now building the production version. Integrates document retrieval, structured agent memory (summaries, user profiles, behavioral signals), and knowledge bases. Requires deep cross-org integration across search, permissioning, roles, and filtering systems.

Qualtrics - Machine Learning Engineer I (August 2024 - May 2025)

  • Supported development and maintenance of the company-wide ML gateway, implementing features for low-latency, high-traffic API serving billions of monthly inferences.
  • Contributed to unified embedding platform development, integrating with Azure OpenAI, AWS Bedrock, and self-hosted SageMaker models.
  • Assisted in deployment of LangGraph platform and established patterns for agentic AI development across teams.

Qualtrics - Software Engineer I (January 2024 - August 2024)

  • Accelerated Machine Learning Infrastructure development for company-wide inference gateway supporting billions of monthly inferences.
  • Led creation of comprehensive embedding API, integrating multiple model vendors and implementing cost tracking mechanisms.
  • Developed internal LLM-powered Slack bot for ticket triage and resolution support across the company.
  • Designed and deployed cost tracking dashboards and automated data collection systems for Monthly Engineering Review.
  • Led creation of on-call runbooks and standard operating procedures for team knowledge transfer.

Qualtrics - Software Engineer Intern (June 2023 - August 2023)

  • Designed and developed the Gradebook Passback feature for Qualtrics LTI 1.3 integration using Node.js, facilitating seamless grade synchronization.
  • Proposed and integrated permissions feature, significantly expanding potential customer base.
  • Executed thorough testing and launch readiness preparation for early access release.

Projects

GTR Pi - (Car) - (Driver) (August 2024 - Current)

  • Collaborated on the development of a Raspberry Pi-powered remote controlled robotic car.
  • Implemented a Python-based API server using FastAPI to manage car operations, including movement commands and status monitoring.
  • Developed a Go-based client application with a web interface to send commands and receive real-time video from the car, enhancing user interaction and control.

Legame (June 2024 - Current)

  • Developed a farming simulation game using C# in Godot, focusing on achieving a maximum farm size, paying off loans, and becoming self-sufficient to retire in the shortest possible time.
  • Implemented mechanics for planting and harvesting various legumes, each with unique growth patterns and special abilities, to create a dynamic and engaging gameplay experience.
  • Designed intricate gameplay systems including inventory management, item drops, legume hybridization, and upgrade paths to provide players with complex strategic choices.

Stark's Industry Mentorship (February 2024 - Current)

  • Mentored students at the University of Florida through tutoring, project management, and mock interviews to enhance their understanding of the tech industry.
  • Led students in industry-standard project lifecycle development, emphasizing agile methodologies, version control best practices, and thorough documentation.
  • Guided a student in developing a full-stack banking application, providing practical experience in real-world software development, including concurrency handling, UI and API design choices, and database management.

Harrison Stark's (My) Website - (Link to Project) (November 2023 - Current)

  • Developed a personal website using HTML, CSS, and JavaScript to effectively present information about my background, skills, and projects.
  • Designed and implemented a user-friendly interface that highlights my professional experience and portfolio.
  • Leveraged the project to enhance my understanding of fundamental web development concepts and improve my proficiency in frontend technologies.

MAISTRO - (Link) - (Frontend) - (Backend) (Fall 2023)

  • Led a team of four in developing an AI DJ using JavaScript and Python, adhering to enterprise software engineering standards.
  • Integrated the Spotify SDK to create a seamless user experience with a unique song recommendation algorithm utilizing the ChatGPT and Spotify APIs and a custom NLP model for emotion and valence extraction.

Quack-end Developer (Summer 2023)

  • Led a team of three in a two-day AI Hackathon to develop an LLM-based rubber duck debugger.
  • Assisted in creating the frontend utilizing React.js and led development of the backend powered by FastAPI.
  • Implemented text-to-speech and speech-to-text using Amazon Polly and Amazon Transcribe, respectively, and used AWS S3 Buckets for rapid input and output.

Only Cats - (Link to Project) (Fall 2022)

  • Developed a video processing program with a partner to remove video frames not containing cats in Python.
  • Utilized a CNN for cat detection in videos, implementing an enhanced EfficientNetB0 architecture.
  • Accelerated unit testing by up to 99% using single images in place of videos.

Traffic Accident Heatmap - (Link to Project) (Spring 2022)

  • Worked in a group of three to create a C++ program to display traffic accidents using the Google Maps API.
  • Adapted dataset of nearly three million traffic accidents from Kaggle which included location and severity.
  • Improved time efficiency of click response and sort by over 90% by utilizing attributes of heaps.

Assembly Simulator - (Link to Project) (Spring 2022)

  • Created an assembly program simulator in C++ for ARM programming.
  • Implemented functionality of 16 ARM commands, along with branching and a program counter.
  • Included ability to produce disassembly and simulation files from binary input.

Pokémon Pokédex - (Link to Project) (Spring 2021)

  • Utilized Java and Swing to create a scrollable GUI Pokédex with information about every Pokémon.
  • Implemented a SQL database using JDBC to fetch and store Pokémon and user information devised from a UML diagram.
  • Improved program incrementally using client-supplied feedback, success criteria, and a Gantt chart.

Landscape Classifier - (Link to Paper) (Spring 2021)

  • Developed a CNN to classify 150x150 RGB images for a research paper: The Effects of Hyperparameter Choices on Convolutional Neural Networks using Python
  • Incorporated elements from the following libraries: TensorFlow, NumPy, and Matplotlib.
  • Determined the most accurate activation function-kernel size pair to be Leaky ReLU and (3, 3).