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5-minute Interview with Fabio Buso

Episode 1: Fabio Buso, VP of Engineering - Hopsworks
December 11, 2023
2 min
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Hopsworks Team
Hopsworks Teamlink to linkedin
Hopsworks Experts

TL;DR

“At Hopsworks, we encounter use-cases that are not necessarily driven by artificial general intelligence (AGI), but rather by business or user experience. Our use-cases help prevent fraud, malicious activities etc., so our goal is to help improve user experience and benefit our users. We want to provide data scientists with the tools they need to deploy their ideas and implementations.” 

In our new ‘5-minute interview’ series we are going to meet AI and ML professionals who will share their experiences on working in the field. How did they start out and what aspects of AI and ML make them tick? What are their passions and what drives them to create major tech innovations? Follow along on this journey to find out!

In our first interview we have a chat with Fabio Buso, VP of Engineering at Hopsworks who is leading the Feature Store development team. Fabio talks about his experience working in the machine learning and data science fields and what drives him to keep building the Hopsworks platform. 

Tell us a little about yourself.

Fabio: 

My name is Fabio Buso, and I lead the engineering team at Hopsworks. I've been with Hopsworks since the early days back in 2017 and I’ve been taking the platform through many different stages. Despite being quite technical, in a start-up environment you wear a lot of hats, but in general my responsibilities involve all aspects of the product's development and maintenance. It is great that I get to interact with users and customers, helping them out, figuring out their problems and how we can resolve them, and coming up with ways to improve the product to bring in more users.

How did you get involved with Hopsworks?

Fabio: 

I actually found out about Hopsworks when I was studying. I was part of a European program during my Master’s degree at KTH (Royal Institute of Technology) in Stockholm and there I met Jim Dowling, CEO and Co-Founder of Hopsworks and started working with him.

At the time, Hopsworks primarily functioned as a machine learning platform. As we expanded the feature store capabilities, it evolved into the core aspect of the platform. Through various iterations and over the years, we naturally progressed, bringing it to the cloud and extending accessibility to a diverse user base. This marked the beginning of my journey with the company.

Why do you think it’s important to work in the Machine Learning field?

Fabio: 

I believe there are two different perspectives on this. On a personal level, having devoted many years to a specific product, it becomes like a cherished project, your ‘baby’ – something you want to nurture and witness flourishing. On a broader scale, my role involves extensive interaction with customers and various users, offering support to help them optimize their experience with Hopsworks. I witness the day-to-day challenges faced by many  data scientists, particularly when transitioning models to production and dealing with data management, both for trained models and, especially, during real-time serving. Assembling a solution that seamlessly caters to their needs is a significant challenge, and that's precisely what we aim to solve at Hopsworks.

Why is Hopsworks a Machine Learning oriented Platform? 

Fabio: 

I think the concept of machine learning solving problems for us is quite interesting. Giving them a bunch of data and getting some results without necessarily having humans in the loop, that’s definitely fascinating. At a high level, the use-cases we encounter everyday are not necessarily driven by artificial general intelligence (AGI), but rather by business or user experience. Our use-cases help prevent fraud, malicious activities etc., so our goal is to help improve user experience and benefit our users. Our goal is to provide data scientists with the tools they need to deploy their ideas and implementations.

As an expert in the field, is there any interesting content that you would recommend?  

Fabio: 

I would like to highlight a very interesting article that we wrote earlier this year called ‘From MLOps to ML Systems with Feature/Training/Inference Pipelines’. This piece provides a high-level overview of our approach to implementing machine learning applications and systems, emphasizing how we harness machine learning to deliver business value. The article delves into the specifics of program structuring and explores how individuals can effectively deploy these programs using Hopsworks.

Want to share your experiences in the AI and ML field with Hopsworks in a future 5-Minute Interview? Feel free to contact us

References

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