Key Contributions
Developed proxy service for Google Cloud Machine Learning APIs
Machine Learning Software Engineer (Intern), 2017
In 2017 SAP and Google launched their strategic partnership. As part of this partnership, the SAP Leonardo platform was extended to support the machine learning functionalities offered by the Google Cloud Platform.
As part of this work stream, I developed a proof of concept service written in Python with Flask which proxied the speech-to-text APIs available on Google Cloud Platform. This involved communication with colleagues at Google and SAP and developing a demo of the service using Jinja and JavaScript, which was presented to the VP in charge of SAP Leonardo.
I worked with a Senior Software Engineer to productionise the service for deployment on SAP's CloudFoundry infrastructure.
Containerised and productionised Abbyy OCR service
Machine Learning Software Engineer (Intern), 2017
As part of SAP's partnership with Abbyy, I worked with a fellow Machine Learning Software Engineering intern to containerise a C++ based OCR service. Once containerised, we developed a python-based wrapper service which enabled communication with the service via a REST interface.
Finally, we documented the service and handed it over to more senior colleagues for further development.
Refactored SAP Leonardo CLI tool to improve UX and i18n
Knowledge Manager (Intern), 2018
Worked with UX specialist colleague to refactor SAP Leonardo ML CLI tool's build process to pull text sources (for labels and descriptions) from a single source. We did this by writing a python script to generate Golang CLI definitions (replacing static definitions) based on a JSON structure containing the text snippets.
This improved the workflow for Knowledge Management staff responsible for in-application documentation and internationalisation by centralising the texts in one place and separating the concerns from the actual