Own large ML engineering projects, Lead and coach other ML engineers: provide guidance in their personal development and help them excel in their projects, Take responsibility for high-quality solutions and deadlines, Understand all the technology which we use for serving ML models live and re-use them for internal tools in the machine learning team, Align with other ML team leads, different teams and overall company management, Implement efficient AI production systems in cooperation with our software developers, Make GPU training and inference scripts faster by profiling bottlenecks and improving them, Own and extend visualization tools used by machine learners, Extend, define and use our internal APIs to gather and transform data and optimally prepare it for ML training, Support our medical team with tooling to efficiently guide the evaluation of annotators and make the annotation process more efficient, Make GPU training robust when training across several servers, You will be directly reporting to the CTO