Putting a Face to the Framework: Hrisi Nedyalkova

Hyperscience | Posted on May 28, 2021

Advances in Machine Learning are at the core of our Hyperscience intelligent automation platform and what we do every day as a team and business. They help bridge the gap between human understanding and machine processing, transforming business operations – and customer experiences – in the process. But how is this technical foundation built?

That’s where Hrisi Nedyalkova comes in. Hrisi is a ML QA Engineering Manager based in Sofia, specializing in application testing. Prior to joining Hyperscience, Hrisi worked in the banking and insurance sectors. She used the communication and data analysis skills she developed in these areas to set herself up for success in the rapidly-evolving field of ML at Hyperscience. 

As we continue to hire for ML talent around the globe, we chatted with Hrisi to learn more about #LifeatHyperscience and what she is most looking forward to. 

What brought you to the field of Machine Learning? Did you always know you wanted to work in this space?

My past experience was actually quite different from ML. I used to work in insurance sales. Although I learned a lot, I was ready for something new and different. 

Since I didn’t have past experience in ML, I wondered if I would be skilled enough for the role at Hyperscience.  But the opportunity sounded interesting – something new and exciting – so I kept pursuing it. Fast forward one and a half years later, and I couldn’t be happier with my choice. 

How did you get up to speed? What kind of training did you receive? 

I have my team to thank for helping me get started. Working with my colleagues is my favorite part of life at Hyperscience. All of the engineers are top-notch and incredibly experienced. They all took the time to onboard me, train me, and ensure I had the insights needed to successfully do my job with confidence.

You became a manager recently. How is that transition going? 

I’m thrilled about my new position! I’m currently managing three people, and we have plans to grow the team this year. Right now, we’re hiring a ML QA Engineer. 

What qualities are you looking for in future ML QA engineers that join the team?

We need people with great attention to detail, as well as quality assurance and data analysis skills. The ideal candidate would be communicative, positive, and eager to learn. Being so curious was what helped me evolve and advance so quickly at Hyperscience, so we definitely value and look for that in new team members. 

What is the biggest challenge that you and your team have worked to overcome over the last year and a half?

The biggest challenge has been building out a trajectory within Engineering that was solely dedicated to Machine Learning. When the team hired me, they knew they needed a QA Engineer who specialized in data analysis, but they weren’t sure what the details of this person’s role would entail. I’ve been carving out that path with my colleagues. 

My team and I perform Quality Assurance on the machine models. We evaluate the quality of the models developed by Engineering and how well they are incorporated into the Hyperscience Platform.  

What steps does the team take to ensure the quality of our platform?

It’s very important that we as QA Engineers really take the time to understand our application. We need to visualize how our customers use it to meet their needs, so weare able to go into the models and evaluate their quality and performance within the application. We’ve also aligned closely with our CX, or Customer Experience, team to learn more about our customers, their unique business needs and how they integrate the Hyperscience Platform into their business operations. 

What’s the most rewarding part of your job?

The end result of my work is really special, and I love seeing the tangible outcomes of all our hard work!  It’s rewarding to see the customer satisfaction and the level of automation and accuracy reached to make our customers, their employees and end customers’ lives easier. 

How have you been staying connected with teammates? [Editor’s Note: While we’re currently fully distributed, we’re constructing a new office in Sofia – more to come!]

Having virtual meetups where we drink coffee online together helps us remain close. We also have the opportunity to participate in different activities organized by the company, which helps me and my team feel connected and inspired at work. 

What’s one piece of advice you’d give to aspiring women in engineering?

Be brave and be curious. For me, at least, the most difficult part was finding the confidence to apply to Hyperscience. I’m really happy that I took a chance and applied for the job. Everyone feels like family here. 

– Hrisi Nedyalkova

BONUS: Lightning round questions

If you weren’t an engineer, what would you be doing instead?

I’d love to work with kids. Kids keep your spirit alive. 

What excites you the most about the future of Hyperscience?

The future is promising for Hyperscience. We’ve transitioned from a company focused on document extraction to an organization completely redefining automation processes. In addition, a product that supports a variety of languages is fascinating we’re currently working on interpreting even more languages! 

Our new office building in Sofia is opening soon, too.  I can’t wait to have a space that enables me to collaborate and brainstorm with my colleagues in person. 

Do you have a favorite productivity hack? 

I love talking with colleagues in the office. Talking with people gives you a new perspective on life. Even laughing with them for five minutes gives me much-needed energy. 

Interested in learning more about the ML field but unsure where to start? Check out Hyperscience Learn an educational program developed by our team aimed at knowledge-sharing and community-building within the ML community. 

Join Some of the Brightest Minds in AI

Turn cutting-edge ML techniques into enterprise-ready AI solutions for the world's largest organizations