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Senior Machine Learning Engineer - Video AI

External
Brainlab logoBrainlab · Munich, Germany
Full-timeOn-siteToday
AWSComputer VisionData AnalysisMachine LearningPython
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Benefits

Health insuranceVision insurancePaid time offFlexible schedule

Additional Information

Work on learning-based solutions for a variety of tasks in medical data analysis with a particular focus on the processing of surgical videos (e.g. event detection, image segmentation, object detection and more) Participate in all phases of the machine learning development life cycle (from requirements engineering and data processing to experimentation, model development/training, and ultimately deployment of solutions) Push the limits of intelligent software components for surgical procedure analysis, making use of the ever increasing amounts of video data Shape the development and productization of AI based video solutions for medical use-cases Contribute to our success with your creative ideas and your independent and self-responsible way of working, ultimately impact the daily work of medical professionals around the world Degree in Computer Science, natural sciences, or similar background 3+ years of professional experience in using modern machine learning methods along with classic computer vision approaches to solve challenging problems in the area of image processing Experience in state-of-the-art ML tooling related to experiment management, containerization, orchestration, processing pipelines and data version control. Profound demonstrated experience in developing complex software systems in Python and/or other programming languages Ideally, you gained this experience during a range of projects in an industrial setting, or you have worked on a PhD in a relevant area Good knowledge in the setup and operation of cloud-based computing environments (ideally AWS) is a plus Experience of working on AI-based products in the med tech industry is a plus A supportive, international team connected by shared values and a culture of trust Meaningful responsibilities with a lasting impact on global healthtech, improving medical decisions and patient outcomes 30 vacation days, plus December 24th and December 31st Flexible working hours and a hybrid work model within Germany Bike leasing via our partner "BikeLeasing" Parking garage and secure underground bike storage Subsidized company restaurant and in‑house café Urban Sports Club membership with employer contribution Regular after‑work, team, and company events Centrally located, modern workspace with a 212 m² rooftop terrace Ready to apply? We look forward to receiving your online application including your first available start date. Contact person: Tatjana von Freyberg


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