Machine Learning Software Developer

Jetzel Espinal

480-***-**** • *************@*****.*** • https://www.linkedin.com/in/jetzelespinal/ • https://github.com/JEspinal01 SUMMARY

Motivated and adaptable software developer with hands-on experience in collaborative, fast paced environments. Skilled in building scalable cloud applications, deploying machine learning models, and integrating end

-to-end software solutions. Eager to contribute to impactful projects, grow within dynamic, cross-functional teams, and start a professional career.

EDUCATION

M.S. Computer Science (Cybersecurity) - Arizona State University, Tempe, AZ (3.71 GPA) May 2025 B.S. Computer Science (Software Engineering) - Arizona State University, Tempe, AZ (3.73 GPA) May 2023 TECHNICAL SKILLS

Languages: Python, C/C++, C#, Java, JavaScript, JSON, HTML/CSS, XML, Bash, SQL, NoSQL, Kotlin Technologies: Github, Unix/Linux, Git, Powershell, VMware, AWS development, Docker, RESTful API’s, PostgreSQL, PyTorch, TensorFlow

PROFESSIONAL EXPERIENCE

Apple Inc. : Specialist, Scottsdale, AZ July 24’ - Jan 25’

● Delivered tailored tech solutions by aligning deep product knowledge with client needs, achieving a 97/100 average Team Member Score and generating multiple referrals to the business team. Geek Squad: Advanced Repair Agent, Mesa, AZ Jan 24’ - July 24’

● Diagnosed and resolved client device hardware/software issues daily, averaging one repair per hour during peak demand and supporting a 1–3 day turnaround goal through clear documentation and team collaboration. Intel Corporation: Network Edge Group (NEX) PTP Engineer Intern, Chandler, AZ July 22’ - Feb. 23’

● Executed 5G base station silicon validation across 5+ systems under test by configuring lab environments with technicians and engineering a Python script to automate chip fuse setup, eliminating manual configuration and improving testing efficiency.

RELEVANT PROJECTS

Multimodal Fake Content Detection System, Info Assurance & Security Spring 2025

● Collaborated on a multimodal fake/AI content detection system leveraging ML and fact-checking APIs; trained XLM-RoBERTa on 70K+ samples to classify text as human- or AI-generated with 93% accuracy on English and 75% on multilingual inputs.

Music Sentiment Analysis Research Project, Statistical Machine Learning Winter 2024

● Led multimodal music sentiment model using BART-fusion, trained on 27K+ songs with 490K+ interpretations to categorize emotion across lyrics, audio, and metadata; supported design and analysis on ASU’s Sol supercomputer.

Auto-Scaling Facial Recognition Application, Cloud Computing Spring 2024

● Developed a facial recognition system using AWS services and Docker containers within a server-less architecture; implemented event-driven workflows with AWS Lambda to automatically process and classify video inputs at scale.

NASA Psyche Web Game, Capstone Project 2022-2023

● Collaborated with a 5-person team on an educational browser-based game for NASA's Psyche mission; implemented a dynamic UI and custom sprite renderer for real-time object modeling.

Contact this candidate