Interdisciplinary software engineer bridging laboratory science and machine learning, building scalable data infrastructure that enables scientists and ML engineers to accelerate research workflows

Software - Designed and built core full-stack architecture for internal LIMS platform leveraging GCP services (Cloud Run, Cloud Storage, etc), Django REST framework, and PostgreSQL, establishing scalable foundation for laboratory data management. App provides single source of truth for all data and an easy UI for scientists and ML engineers to interface with

Data eng - Engineered automated data pipelines by integrating APIs from external sequencing vendors (Illumina + Nanopore) and implementing bidirectional data synchronization between on-prem lab instruments and our internal LIMS / Benchling. All systems are deployed using infrastructure-as-code. (Terraform) and instrumented with traces & alerts using OpenTelemetry (OTel)

Bioinformatics - Developed and maintain bioinformatics analysis pipelines for NGS data processing, variant calling, and quality control, implementing containerized workflows using Docker and orchestration tools for reproducible computational research

Early software engineer who built Impossible Foods' first centralized data platform and established software engineering practices for the data science team

Software - Designed and built Impossible Foods' first centralized data management system, replacing isolated spreadsheets with a containerized Django app on Cloud Run + MySQL. Created simple web UI for scientists to enter data and upload files, plus API endpoints for programmatic access and third-party integration. Transition to structured data increased reliability and enabled cross-functional teams to readily search and visualize their data

Data eng - Engineered Google Cloud ETL pipelines using Cloud Functions, Cloud Pub/Sub, Cloud Scheduler, and Dataproc to automate data ingestion and processing workflows across the organization

Mentorship - Laid software best practices foundation for the software-data science team by creating documentation, establishing pair coding sessions, and implementing code review processes. Balanced activation energy and potential return of each best practice to generate viable implementation plans suited for a small startup team

Bioinformatics - Performed bioinformatics analysis of internal strains (whole genome assembly & variant calling) and contributed bioinformatic analysis for regulatory approval in global markets

100% software. Transitioned to the Software team. Tasks included:

50% software / 50% lab-based R&D work - based on the R&D team

As a member of the Interdisciplinary Computing and Complex BioSystems (ICOS) research group, I worked on the EPSRC-funded Newcastle University Frontiers in Engineering Biology (NUFEB) project. The NUFEB project aims to engineer wastewater microbial communities for enhanced micro-pollutant degradation.

I contributed to the project both within the lab and software based, with my main contribution being the development, and in vivo validation, of a Python toolkit to aid the genetic engineering of bacterial communities via a multiplex CRISPR-Cas9 approach.