ANNT member Adnan Mehremić tells us his career story and invites secondary school students to apply for STEM Youth Camp 2022 (https://www.annt.ba/bs/article/89/stem-youth-camp-syc-2022 ).
“I currently work as a Machine Learning Engineer in the field of artificial intelligence. My working day begins with a meeting where, with my team, I discuss the tasks we worked on the previous day and will work on that day, as well as possible blockers. Designing machine learning systems requires a machine learning engineer to analyse and organise data and optimise learning algorithms in order to obtain a high-performance machine learning model as a result. As the most exciting part of the job I would definitely single out developing algorithms that have the ability to learn and make predictions/decisions independently. For this field you simply have to be multidisciplinary, because it requires knowledge of statistics, probability, data structures, algorithms, programming, cloud services, etc.
Among the most important skills for working as a Machine Learning Engineer, I would single out an inclination towards research, followed by programming and a good knowledge of mathematics, algorithms and data structures. The next step in my career is Senior Machine Learning Engineer, and then Machine Learning Consultant. Given that we live in a time when the amount of data is growing rapidly, and ever more data will be generated in the future, the best tools for analysing „Big data“ are Machine/deep learning algorithms.
I finished the Secondary School of Electrical Engineering, and the natural path for continuing my education was the Faculty of Electrical Engineering. My expectation was that I would become an expert in the field I would study for the next 5 years; however, after completing my master's studies I realised that I was only at the beginning of learning, and that university only shows you where the keys are to the doors behind which lie unexplored areas that you have merely „scratched the surface of“ during your studies. I am guided by the saying: ‘You can't know everything, but you can learn anything.’. What should be improved at universities is that academic knowledge should be as close as possible to the skills needed in industry.”
