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Jobs / Snke

Senior Machine Learning Engineer – Video AI

Snke · Münchensenior

In short

  • ▸Desarrollar modelos de IA para analizar videos quirúrgicos y sensores en tiempo real.
  • ▸Trabajar en todo el ciclo de vida del ML: desde datos hasta despliegue en producción con alto impacto clínico.
  • ▸Impacto directo en la eficiencia y seguridad de procedimientos quirúrgicos a nivel global.

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What they ask for

  • ✓3+ años de experiencia en ML y visión por computadora aplicados al análisis de imágenes.
  • ✓Experiencia demostrable en desarrollo de sistemas de software complejos con Python.
  • ✓Conocimiento en plataformas de ML modernas: experiment management, orquestación, pipelines, versionado de datos.
  • ✓Experiencia en entornos en la nube (AWS idealmente).
  • ✓Experiencia previa en productos de IA para salud (med tech) es un plus.
  • ✓Formación en Ciencias de la Computación, Ciencias Naturales o similar.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonAWSExperiment ManagementContainerizationOrchestrationData Version ControlProcessing PipelinesMachine LearningComputer VisionCloud-Based Computing

Who should you write to at Snke?

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What you'll do As (Senior) Machine Learning – Video AI at Snke you will develop and deploy machine learning applications that analyze video and sensor data from the operating room to improve surgical workflows. You will work closely with software developers and ML engineers to build services on the Snke platform that extract meaningful insights and enable smarter, more efficient, and safer surgical procedures. In addition, you will leverage modern ML training platforms and strong software engineering skills to drive innovation in intelligent assistance tools and automation. 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 What we're looking for 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 Why Snke 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.

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