Team AI
Hey! Nice to meet you
AI - We Can Explain!
The central pursuit of Team AI is to empower Axel Springer universe with AI-backed systems. We strive to achieve this goal by building products and services that leverage State-Of-The-Art techniques in the areas of Deep Learning, MLOps, Data Engineering and Software Engineering. We believe in being community-facing. To that end, we have developed several Open-Source Projects and regularly share our learnings through talks and blogs. As a team, we offer Machine Learning expertise in the areas of Natural Language Processing, Speech & Audio Processing and Computer Vision.
The Team
Tanuj Jain
I work as a Machine Learning Engineer in Team AI. Having worked in the field for several years, I have hands-on experience with use cases employing classical Machine Learning techniques, Computer Vision, Audio/Speech processing as well as Natural Language Processing. My current areas of interest comprise MLOps and Natural Language Processing. I like exploring new data-related tools and building small day-to-day applications for my personal use. In my non-work time, I vacillate between being a couch potato and working out. Other activities I enjoy are honing my half-dead guitar-playing skills and watching movies.
Oleksii Oliinyk
I work as an ML Engineer in Team AI at Ideas Engineering. My background is in Computer Science with a couple of years of Software Engineering where I transitioned from Web Development to Mobile Development. Then I did Master studies in the field of AI and made a shift it my carrier towards Machine Learning. In the recent years I got industry experience which consists mostly of Computer Vision related projects. My current focus at Ideas Engineering is at NLP, TTS, and MLOps. Apart from IT-related topics, I'm interested in Art, hiking, and traveling of different kinds.
Christian Schäfer
Currently I am researching and implementing ML pipelines with focus on NLP and audio processing. My professional interests moved from network theory (physics) over neuroscience to deep learning, which all share some interesting similarities.
Most of my private time is devoted to my two kids and what's left is being spent hitting either yellow or orange/blue balls over a net.