(Senior) Machine Learning Engineer – Video AI

BrainlabMunich, BY, Germany
FULL_TIME
Mid-Senior Level
Engineering
  • 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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