A Celebration of Women's History Month with Andreea, Senior MLOps Engineer at TR Labs

March 8th marks International Women’s Day, a global initiative dedicated to acknowledging and celebrating the social, economic, cultural, and political achievements of women and girls worldwide. This significant day also serves as a platform to raise awareness about the strides made towards achieving gender equality, while recognizing the ongoing efforts required to bridge existing gaps.

In honor of Women’s History Month, we had the privilege of interviewing Andreea, a Senior Machine Learning Operations (MLOps) Engineer for TR Labs based in Zug, Switzerland. TR Labs stands as the dedicated applied research division of Thomson Reuters, where our focus lies in the research, development, and application of AI and emerging trends in technology.

 

 

Why did you want to join TR Labs?

I began my professional journey with Thomson Reuters as an intern. I joined TR Labs with the goal of implementing the knowledge and skills acquired during my academic journey in a relevant domain. I knew that TR Labs was an ideal opportunity for anyone wanting to engage with the forefront of technological advancements and would help me grow personally and professionally.

 

What have been some of the problems you are solving in your role?

Since joining the team, I’ve tackled many challenges spanning the diverse domains we manage at Thomson Reuters, from news and social media to legal offerings. More recently, I have been working on the adoption of Machine Learning Operations (MLOps) processes. TR Labs developed and is continually improving a solid toolchain (a set of software development tools used simultaneously to complete complex software development tasks) that allows for efficient research and experimentation, with a straightforward path to maturation into repeatable and highly automated pipelines.

The existing toolchain that we are continually refining within TR Labs injects maturity into our operations, greatly enhancing the transition rate of ML projects from the research phase to their integration into production-grade systems. The pace of change in this sector is rapid, making it critical to consistently adopt and support the latest technologies and tools.

 

What has your career progression been at Thomson Reuters? How have you been able to develop your skills here?

Following my internship with TR Labs, I was presented with the opportunity to become a part of the team as a Software Engineer. As a Software Engineer, I had the privilege of engaging with a diverse range of projects, each requiring the application of distinct technologies, frameworks, and toolchains. Thomson Reuters provided an environment that fostered my growth and development, consistently offering opportunities for continuous learning and staying current with the most recent trends in technology.

Two years ago, I decided to undertake a new challenge and pursue a Master’s degree in AI. These past two challenging and rewarding years have flown by quickly, and I feel incredibly privileged to have spent them growing my love for Software Engineering and AI. I am eager to continue applying the knowledge I’ve gained in my work with TR Labs, contributing to innovation for our customers and informing the way forward.

 

Can you share more about your experience in the Women at Thomson Reuters Zug chapter?

I joined the Women at Thomson Reuters business resource group after attending one of their events. It was apparent how much this group was influencing the professional growth and development of its members, and I wanted to be a part of it. I am now the co-lead of events for the Zug chapter. I’ve had the opportunity to spearhead initiatives such as speed networking sessions, storytelling workshops led by senior leaders, International Women’s Day events, and seminars for parents to help balance work and family life.

Beyond this, being a member of this business resource group provides the opportunity to enhance one’s professional network, increasing allyship and driving awareness of the unconscious biases that fuel gender inequality.​​​​​​​

 

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