backend

Brainlab

<div><section><div><p></p><h2>Company Description</h2></div><div><p>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, enablin and holistic—helping healthcare providers deliver meaningful change.</p></div></section><section><div><p></p><h2>Job Description</h2></div><div><p>For our ambitious and growing Snke Anatomy department, we are looking for a machine learning platform engineer with a strong background in building state-of-the-art MLOps infrastructure.</p><p>In this position, you will:</p><ul><li>shape the development and productization of AI-based solutions for medical use-cases</li><li>design, build, and maintain systems to enable complex development workflows throughout the machine learning life cycle (from data processing to experimentation, model training, and evaluation)</li><li>set up and operate complex computing environments based on local and cloud resources, using modern DevOps / MLOps techniques</li><li>work closely with our machine learning engineers to establish new standards in development efficiency, automation, and reproducibility</li><li>set up processing pipelines to make complex medical data accessible in the best possible way</li></ul></div></section><section><div><p></p><h2>Qualifications</h2></div><div><ul><li>Education in Computer Science, natural sciences, or similar background</li><li>Demonstrated experience in designing complex computing environments based on Linux and ideally Windows, including solid understanding of networking, storage, and authentication concepts as well as infrastructure-as-code technologies (e.g., Ansible and/or Terraform)</li><li>Proven experience setting up and maintaining container (i.e. Docker) orchestration tools (in particular Kubernetes) and container management</li><li>Track record of working on CI/CD (e.g., Github actions)</li><li>Good knowledge in the setup and operation of cloud-based computing environments (ideally AWS)</li><li>Good understanding of the success factors for modern software development (ideally in the context of machine learning) and a strong agile DevOps mindset</li><li>Broad knowledge of the ML/DL development process and data pipelines</li><li>Solid programming experience in Python; C++ is a plus</li></ul></div></section><section><div><p></p><h2>Additional Information</h2></div><div><ul><li>A mutually-supportive, international team</li><li>Opportunity to build career experience in an exciting international company with a lasting impact on medical technology based in Munich<strong> </strong></li><li>Flexible working hours</li><li>Secure bicycle storage room</li><li>Subsidized catering service </li><li>Subsidized Gold Gym membership and access to Brainlab headquarters modern gym</li><li>Centrally located, modern work spaces with a great 212m² roof terrace</li></ul><p>Ready to apply? We look forward to receiving your online application including your first available start date.</p><p>Contact person: Daniel Sypli</p></div></section></div>

(Senior) Machine Learning Platform Engineer