AI/ML Engineer (m/ž)

We are looking for a talented Machine Learning/AI Engineer to join our team working on different projects mainly related to timeseries forecasting. If you are passionate about applying machine learning/AI algorithms in real-industry problems, to provide accurate timeseries predictions for electricity price, carbon price, solar power plant production or stocks price, Uprise is the place to be. If you are familiar with the terms such as LSTM, RNN, CNN, K-means, DBScan, Holt-Winters, Transfer learning or Random Forest you might be excellent addition to our team. You will as well have a chance to participate in international research projects. About the team We are a Zagreb-based young team of hard-working and enthusiastic experts located right in the city center in the beautiful new offices, dedicated to providing custom software development and other product lifecycle services, which includes both internal and external projects. We are big supporters of proactiveness and are always open to support innovative ideas. What will you do at Uprise: - Working on the projects that include components based on the machine learning or AI (with focus on timeseries forecasting) - Closely collaborate with product managers and business analysts from the energy and finance sectors, and other software engineers - Mentor more junior colleagues in our team - Suggesting and providing key inputs when deciding upon technical approach for solution - Write clean, efficient, and sustainable code - Come up with efficient and creative algorithms for complex problems

What we are looking for: - 3+ years of experience working on machine learning/AI projects - Masters in Computer Science, Mathematics, Statistics, or another related field - Familiarity with Python, Tensorflow, Keras, Scikit, PyTorch, MySQL - Having experience with machine learning and deep learning deployment, and training methods is a bonus - Familiarity with Git - Team player, proactive, thoughtful and efficient problem solver - You are able to perform independently or in a small team - A pragmatic approach, biased to simplicity, where you most care about achieving impact - Fluent in English