Senior Machine Learning Engineer – Video AI

What you'll do

As Senior Machine Learning Engineer 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.• 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

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 salary expectations and earliest possible start date. We welcome applications from people of all backgrounds and identities. Diverse perspectives help us build smarter solutions and improve patient outcomes. Contact person

Tatjana von Freyberg About us

Founded in 2020 and headquartered in Munich, Snke is transforming healthtech with scalable, data-driven innovation powered by AI and big data analytics. We're experts specializing in large platforms, digital health and software-driven medical technology. By delivering a trusted orchestration layer, Snke empowers healthcare providers, societies, registries, agencies and all partners to deploy cutting-edge solutions for safe and efficient interventions and enhances patient outcomes. Beyond our Munich headquarters, we have core teams in Chicago, Heidelberg, San Diego and Tel Aviv. Snke fosters global collaboration to create technologies that are smart, enabling and holistic-helping healthcare providers deliver meaningful change.