// Summary
Backend engineer with 4 years experience in building distributed data systems at scale, and a research background in machine learning and computational biology — including a publication at MICCAI 2022. Experienced in Java and Python across both production systems and research workflows. Looking to move into a role where engineering and research intersect.
// Experience
Veeva Systems · San Francisco, CA
- Engineered distributed sync infrastructure serving hundreds of thousands of records, supporting both full-refresh and incremental data synchronization between cloud and offline-capable client devices.
- Designed and implemented processing logic for internal upload pipelines to handle specialized record types — including net-new API endpoints for novel upload flows — defining API contracts across multiple product teams and ensuring correctness at scale.
- Contributed to a large-scale platform migration from a Salesforce-based legacy system to an internal native platform, rewriting and validating sync services to preserve data integrity across the transition.
- Built reactive, asynchronous backend services in Java within a distributed systems environment; with exposure to Kafka and Spark-based messaging and data processing, Hazelcast-backed state management, and observability tooling via Prometheus and Jaeger.
- Served as a cross-functional collaborator between the sync team and several product teams, translating product requirements into backend data contracts and system behavior.
Bionic Vision Lab · UCSB
- Developed a greedy optimization framework in Python using dictionary learning and evolutionary algorithms to maximize visual subfield coverage in epiretinal prostheses; work accepted and published at MICCAI 2022.
Dynamic Networks: Analysis and Modeling Lab · UCSB
- Contributed to ongoing research modeling signed time-series graph data to represent group dynamics, developing graph-based representations of interpersonal interactions using deep learning techniques.
- Applied deep learning to molecular data to learn rich embeddings, gaining hands-on experience and building ML pipelines using Pandas and NumPy.
Cal Poly, SLO · UCSB
- Designed and executed data science projects that analyzed real-world datasets to apply topics in machine learning, statistics, and data visualization.
- Led discussion sections, hosted office hours, and conducted workshops on topics in Biology, Chemistry, Physics, and Computer Science.
- Created and delivered project, lecture, and course materials to students.
// Education
M.S. Computer Science
University of California, Santa Barbara
A.S. Computer Science
Cuesta College, San Luis Obispo
B.S. Biological Sciences, Biotechnology Minor
California Polytechnic State University, San Luis Obispo