Zachary Munro

Lead Software Engineer, MLOps & Machine Learning

• Engineered a comprehensive machine learning development suite to enhance experiment execution, model deployment, data modeling, and analyst workflow support.
• Spearheaded the redesign and migration of analytical database schemas from on-prem SQLServer to Snowflake, leveraging Fivetran for efficient data transition.

Technologies:

Python, MLFlow, DBT, Docker, AWS, Snowflake

Senior Software Engineer, MLOps

• Redesigned and migrated data ingestion tools to AWS Lambda, significantly reducing costs and improving performance.
• Developed a new data ingestion and featurization pipeline using DBT, achieving a tenfold increase in ingestion speeds by replacing SQL Server stored procedures.

Technologies:

Python, Docker, SQLServer, DBT, AWS, Snowflake

Data Engineer 2

• Developed dozens of novel ETL workflows for handling laboratory equipment data from various vendors, machines, and software.
• Created benchmarking pipelines in Python for optimizing file latency in data workflows, resulting in a 20% processing speed boost.
• Built and designed internal web application for managing company data, resulting in greater database visibility for 200+ people on sales and development teams.

Technologies:

Python, C#, PostgreSQL, Docker, JavaScript, AWS (S3 + RDS + EC2)

Software Engineer II

• Developed a cloud application for a monolithic product utilizing serverless methodologies in AWS using Java and Python.
• Built highly scalable and distributed testing and deployment infrastructure to handle 100+ daily CI pipeline executions.

Technologies:

Java, Python, React, TypeScript, Github CI, Docker, PostgreSQL, AWS (API Gateway + Lambda + S3)

Software Engineer

• Designed a novel statistical DNA data correction tool used for preparing data for rapid ML antibiotic resistance prediction, reducing overall prediction time by 40% and increasing accuracy by over 20%.
• Rebuilt and redesigned monolithic Python bioinformatics pipelines into distributed parallelized cloud dataflows increasing throughput by 60x.
• Created cloud bioinformatics APIs using Python for processing clinical NGS data.
• Worked closely with Data Scientists and Researchers to build Python packages, APIs, and data pipelines to facilitate their research and bring their work into production.

Technologies:

Python + Pandas, Docker, GCP, Kubernetes, JavaScript, PostgreSQL, C++, Prefect, Argo, CircleCI

Publications:

rapid Ultra-high Enrichment of Bacterial Pathogens at Low Concentration from Blood for Species ID and AMR Prediction Using Nanopore Sequencing

pilot Study of a Novel Whole-genome Sequencing Based Rapid Bacterial Identification Assay in Patients with Bacteremia

Undergraduate Researcher

• Developed an incremental language parsing system and an anticipatory cognitive model to replicate a human’s ability to predict meaning and the ideal time to begin their dialogue turn.
• Designed computational cognitive models of dialogue processing able to generate and produce responses to questions in under 200ms.

Technologies:

Python, Java