Built software components for 17 different machine learning tools for a Series D startup with a $1.4B+ valuation providing preventative maintenance and natural language processing (NLP) products to B2B clients

Identified tools to add to the continuous integration (CI) process to improve the code quality for the Engineering Team of 30+ developers by requiring test runs and security checks in automated Jenkins builds

Oversaw six cloud-based NLP based API applications as the Scrum Master for a team of six developers and launched the products with two B2B clients

Led daily standups, managed a JIRA ticket board, and executed a regular release cadence as the Scrum Master to launch new feature requests and bug resolutions utilizing the agile software development practice

Created a visualization tool as the sole backend engineer using graph databases, allowing manufacturing clients to inspect their physical assets and identify patterns in their data that could lead to cost-saving measures

Established transparency on the backend architecture design and the resources required to meet customer deadlines by communicating with the Engineering Lead and the respective product owners

Automated the standard reporting process to clients by self-learning Python, saving time for employees in a manufacturing company building railroad maintenance equipment

Applied machine learning applications to accurately assess the condition of railroad ties, replacing custom-made algorithms that were complex and hard to maintain

Examined, maintained, and installed equipment by traveling across the country, explaining technical information to non-technical external clients