Internships at Radix: Martin’s Machine Learning Engineer story
As a rapidly developing, ambitious company, we continuously take on new challenges when it comes to our consulting services and our products. This makes Radix an exciting place to be, especially when you are fond of innovative technologies and want to develop your career in this field.
This is why we make sure that we provide opportunities for the young talent to contribute to the Artificial Intelligence scene in Belgium – we offer internship placements for several motivated people throughout the year. How does it work, and what do you learn? Who are the people that get the internship?
Say no more! Here is the story of Martin Seyferth, who has just completed his three months internship at Radix. See for yourself what is his story, how his experience has transformed his career expectations and decide if you’re up for the same challenge.
Radix: Did you always know what you wanted to do with your life? Where did your interest in technology start?
Martin: I loved mathematics from first grade in elementary school and was lucky enough to have teachers who supported my thirst of knowledge. From middle school, I knew I wanted to work in a field that affects people’s everyday lives but still being complex enough to challenge me on a mathematical level. While studying, I was introduced to programming and the tremendous overlap between machine learning and mathematics. While it fulfilled my desire to solve complex problems, it also affects our everyday lives, so it was a perfect fit for me.
R: Where did you previously study, and what were your favorite subjects?
M: I studied Mathematics at Humboldt University in Berlin. I chose to live in Berlin because it is a vibrant, diverse city. My education has not only given me the mathematical toolset to solve machine learning problems, but also a structured way of approaching problems. I also learned the fundamentals of scientific programming. On the soft-skill side, I assume what helps me most is the ability to not despair of problems that seem to be unsolvable at first sight.
R: What precisely of what you learned helps you in your internship now?
M: The work at Radix is very evidence-driven, so it helped me a lot to be able to formulate conclusive hypotheses and verify them based on quantitative and qualitative results. I was also working in backend development, and that taught me how to write clean and maintainable code, I wanted to proceed with that while applying my mathematical knowledge.
R: What was the moment you knew you’d made the right decision to take an internship at Radix?
M: I think I knew even before I started. The hiring interviews were challenging for me, but the interviewers were supportive. Even if I did not know the correct answer to a question, it was explained in the interview, and I saw how much I could learn from the people working at Radix. Other than that, I was sure when I saw how much dedication went into individual projects.
R: What were your responsibilities during this internship, what projects did you work on, how did you interact with the team?
M: The main project was to create a package that could evaluate TalentAPI’s performance for clients based on objective measurements. Based on that, I took the baseline performance for a client and dug into the setup of a specific client to see if there was room for improvement. Furthermore, I created a package that automatically tries to find the best configuration.
R: What were the best moments during the internship for you? What did you love most about it?
M: Speaking of a single event, I would say that I was allowed to present my findings to a client and explain how I think they improved their account. The experience showed Radix trusted me and valued my contribution. Some very good moments were also when the engineers sat together to discuss observations that seemed unexplainable. It felt like solving riddles all together!
R: What’s something that happened that can only happen here at Radix?
M: Doing push-ups after a deal is closed, everyone was so excited and pumped, that was amazing.
R: What are you most proud of as an internship accomplishment?
M: Having code that was shipped to production and creating packages that will hopefully be used by either future interns or other Radix employees.
R: Tell me about the interactions with the team. How did it work in the context of the current pandemic?
M: It was not an easy situation being onboarded on remote and on a strict lockdown, but everyone from the team was eager to help me with every question that I had, which on the one hand gave me the feeling that the team cares about me and on the other hand valued my contribution.
R: How do you help people with what you did at Radix? What is the overall value of what you do and how do you feel about it?
M: The work that I have done will mostly contribute to making better decisions if one algorithm is favorable in terms of quantitative results. I hope that my other project will be used to find optimal configurations for clients that have been using the platform for a while and keep them happy with results.
Overall, the work I did was challenging, but being challenged continuously pushed me to a level of understanding that I did not expect to have at the beginning of the internship. What surprised me most was how driven people were by explainability and creating transparency on all levels of the company. I mean this is not only applicable to machine learning solutions, but to the whole company in its daily business, that impressed me very much.
R: If you could describe the internship in 3 adjectives, what would they be?
M: If I had to pick just three, I’d say challenging, rewarding, and awesome.
Challenging, rewarding, awesome. Sounds like something you would be up to? Don’t hesitate to contact us for an internship placement for next summer. We will be excited to provide you with a rich practical experience and of course, lots of team fun!