Nellie Cordova

About me

Clear problems. Clean data. Real impact.

Hi—I'm Nellie.

Curious, practical, outcome-oriented.

I'm a software engineer with production experience and a strong machine learning foundation, currently completing an M.S. in Computer Science (Machine Learning). I like building systems that are useful, measurable, and maintainable.

Lately, I’ve been building applied ML/LLM projects that blend vision, natural language processing, and retrieval (RAG) to ship end-to-end prototypes as API-first services—with clear interfaces, evaluation, and guardrails.

Previously, I worked on a real-time payments platform, contributing to Java microservices, test automation, CI quality gates, and regulated release processes. That experience shaped how I think about reliability, monitoring, and software that is safe to ship.

I'm open to AI/ML Engineer and Backend/SWE roles—especially teams building production LLM features, data/ML services, or backend systems with real constraints. If that’s you, I’d love to connect.

Specialization ML-oriented SWE

Experience Level Mid-level SWE
ML: hands-on projects + graduate specialization

Education M.S. CS (ML), Georgia Tech — in progress

Languages English, Spanish

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Resume

Professional Summary

Software engineer with production experience in Java microservices on a real-time payments platform and an M.S. CS (ML) in progress. I build deployable ML/LLM services end-to-end (APIs, evaluation, guardrails), and bring strong testing automation, CI quality gates, and release readiness.

Comfortable with experiment design and metrics-driven iteration (offline evaluation, error analysis, and targeted improvements).

Information

Technical Skills

Languages — Python (primary) · Java · SQL · R · C++ (academic)

Backend & APIs — FastAPI · REST APIs · Pydantic · typed request/response models

Quality & Delivery — CI/CD (Jenkins, Maven) · automated testing (JUnit/Cucumber) · API/perf testing (Postman, SOAP UI, JMeter) · release readiness

Cloud & Ops — Docker · AWS (AI Practitioner) · monitoring/alerting · runbooks

LLM / RAG / Agents — RAG pipelines (retrieval, reranking, citations) · evaluation & guardrails · prompt/tool workflows · OpenAI Agents SDK · LangChain (exploratory)

ML Foundations — PyTorch · scikit-learn · Transformers · NumPy · pandas · classification · fine-tuning & transfer learning · sequence models (RNN/LSTM, seq2seq) · attention / memory networks

Data & Evaluation — experiment design · cross-validation · data preprocessing/augmentation · metrics (F1, RMSE, perplexity) · error analysis · visualization (Matplotlib)

Developer Tools — Git · Jupyter · VS Code · IntelliJ · JIRA · Bitbucket · Confluence

Other — English & Spanish (bilingual)

Professional Experience

Software Engineer

JPMorgan Chase & Co. | Tampa, FL

2019 - 2021

Real-Time Payments Platform

Contributed end-to-end across the SDLC for Java-based payments microservices and drove production readiness.
Authored comprehensive operational runbooks—architecture, dependencies/configs, failure modes, diagnostic checklists, and step-by-step remediation—to enable fast triage, recovery, and self-serve on-call; provided light support on monitoring/alerting dashboards with platform/SRE.
Built and maintained test automation (JUnit, Cucumber); enforced CI quality gates (tests, static analysis, coverage) to keep merges green, and executed functional/perf testing (Postman, SOAP UI, JMeter).
Managed regulated releases: compiled release evidence (test/coverage reports, change tickets, approvals) to secure production sign-off; presented services to global production management.
Led/participated in agile rituals (sprint planning, backlog refinement); authored technical docs; coordinated across time zones.

2019 - 2020

Salesforce Platform

Delivered Salesforce CRM data-collection and reporting features for a social-impact organization.
Gathered stakeholder requirements and translated them into schema updates, UI changes, and documented technical implementations.
Expanded the underlying data model by adding new objects, fields, and relationships, and updated the custom Visualforce UI to align with the revised schema for accurate structured data capture.
Contributed a small Flow-based automation to digitize an existing paper survey, enabling standardized survey generation within the CRM.

ML Research Assistant

CS Dept. @ William Paterson University | Wayne, NJ

2018 - 2019

Applied exploratory data analysis and knowledge discovery to augment prior hypothesis-driven work on teen tanning behaviors.
Implemented and evaluated predictive models (KNN, Logistic Regression, clustering) in Python/R.
Presented insights to faculty and students.

Education

M.S. in Computer Science (Machine Learning)

Georgia Institute of Technology | Atlanta, GA

2022 - Present

Relevant Coursework: Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Network Science

B.A. in Mathematics | Minor: Computer Science

William Paterson University | Wayne, NJ

2016 - 2019

Relevant Coursework: Database Management Systems, Data Warehouse & Data Mining, Cloud Computing, Applied Regression Analysis

Magna Cum Laude • Pi Mu Epsilon (National Mathematics Honor Society)

Certifications

AWS Certified AI Practitioner

2025 - 2028

Group 2 Social / Behavioral Research Investigators and Key Personnel

CITI Program

2024 - 2027

SWE Resume ML Resume

SWE Preview ML Preview

Projects

All Projects
AI
DL
NLP
UX
Backend / Systems

ProductLens

LLM-driven product comparison tool that ranks products based on user priorities.

GenAI LLM OpenAI Agents SDK Gradio UI

Professional TwinBot AI

AI-powered resume-grounded assistant: tool-style prompting + retrieval patterns for accurate, personalized responses.

GenAI LLM Chatbot Gradio UI

Modular RAG (v2)

Modular, flow-based RAG framework evolved from a monolithic RAG system, designed for hybrid retrieval, explicit orchestration, and agentic extensibility.

FastAPI Hybrid retrieval FAISS LLM