Meet the Team: Charlene Leong, ML Engineer & Data Scientist

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What I’m doing at Relevance AI

Hello, my name is Charlene, and I’m currently a Machine Learning Engineer/Data Scientist at Relevance AI. During my time here, I’ve worked on everything from product feature R&D, marketing collateral, documentation, client work, to productionising our data science/ML solutions.

My responsibility at Relevance ranges from building POCs for clients, solution engineering and data analysis, writing documentation, building and testing new features, productionising our data science/ML infrastructure, helping with content marketing to working on the codebase.

My career journey to Relevance AI

After a few stints in ML R&D and tech consulting, I became interested in learning how to productionise ML solutions and decided to pursue cloud engineering to grow such a foundation. This experience gave me exposure to different domains, verticals, tech stacks and environments, which has proven invaluable.

In this time of Covid, I became interested in how this technology shift has impacted people and the workforce, and the future of work, which brought me over from NZ to Sydney to join a start-up innovating in this space.

I then moved onto an ML/MLOps Engineering role working in an innovation team at the NBN, POCing MLOps solutions, re-architecting the DS/ML platform and informing ML team structure to uplift business processes, to increase revenue and reduce costs.

What I’m most excited about working at Relevance AI

I’m interested in helping organisations make insightful use of their unstructured data to make impactful business decisions, especially from a next-gen ML/data stack and system perspective- ML and MLOps is a maturing industry, and bringing ML analytics to the masses through marrying the world of AI and BI is a fascinating place to be in. I’m excited about bringing POC to product, seeing how Relevance can help customers solve complex needle-moving problems, learning about early-stage startup growth and the journey in finding product-market fit.

What my average day at Relevance AI looks like

My days vary from day to day, but it often involves a mixture of starting the day with some reading and research and then deep diving into coding or data analysis in the morning. I collaborate with frontend/SDK/API/infra teams to identify blockers, changes, and new development required to build new features in the product requested by customers. I end with reflecting on how we can improve our product and experience for our end users.

What I do outside of work

When I’m not at work, I enjoy hiking, diving, and exploring Sydney’s surrounding beaches, mountains and wildlife!

Meet the Team: Charlene Leong, ML Engineer & Data Scientist
Elaha Gurgani
May 6, 2022
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