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Machine Learning Engineer (all genders)

Avelios Medical

München

Vor Ort

EUR 60.000 - 100.000

Vollzeit

Vor 13 Tagen

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Zusammenfassung

An innovative company is seeking a (Senior) Machine Learning Engineer to join their dynamic team in Munich. This role focuses on implementing cutting-edge Machine Learning models to enhance healthcare delivery. You will work directly with a talented development team, utilizing state-of-the-art technologies to optimize workflows in hospitals. The position offers a motivating work environment, access to high-performance computing resources, and the chance to make a significant impact on patient care. If you're passionate about technology and eager to contribute to a meaningful mission, this is the perfect opportunity for you.

Leistungen

Flexible Arbeitszeiten
Startup-Umfeld
Diverse Team
Virtuelles Aktienoptionspaket
Zentrale Lage in München

Qualifikationen

  • Studienabschluss in Informatik oder gleichwertige praktische Erfahrung.
  • Erfahrung in der Anwendung von Machine Learning Modellen.

Aufgaben

  • Entwicklung und Integration von Machine Learning in medizinische Arbeitsabläufe.
  • Arbeiten mit großen klinischen Datensätzen zur Modellentwicklung.

Kenntnisse

Machine Learning
PyTorch
TensorFlow
Keras
Git
Computer Vision
Natural Language Processing (NLP)

Ausbildung

Informatik oder Computerwissenschaften

Tools

High Performance Computing

Jobbeschreibung

Festanstellung, Vollzeit

  • München

About This Role

Our mission at Avelios is to build the leading software platform for the data-driven digitization of hospitals and patient care. To do so, we have built a modular software platform that digitizes and optimizes workflows in hospitals with cutting-edge technology in a user-friendly way. With our software, we enable hospitals, doctors & nurses to provide their patients with the best possible care.

To continue to shape the future of healthcare, we are looking for a (Senior) Machine Learning Engineer as a key member of our development and research team. Your focus will be on implementing state-of-the-art Machine Learning models in a critical environment and working on large-scale infrastructure.

Your Responsibilities

  • Work directly with our core development team
  • Design and train models on large-scale clinical datasets
  • Integrate Machine Learning into medical workflows
  • Work with Federated Machine Learning
  • Work together with top research facilities
  • Have access to high performance computing infrastructure

Your Qualifications

  • Studies in Informatics or Computer Science from a top university or equivalent practical experience
  • Experience in one or more: PyTorch, Tensorflow or Keras
  • Publications on top conferences or demonstrated state-of-the-art results in Machine Learning applications (Computer Vision and/or NLP)
  • Relevant coding experience (GitHub contributions beneficial)
  • Interest in learning new technologies
  • Fluency in German or English

Your Benefits

  • A deep understanding of our technologies and proficiency in our modern & relevant tech stack
  • Ability to gain valuable hands-on experience in a startup backed by top European VCs
  • High flexibility, variety in your tasks and the opportunity to take ownership
  • Motivating work environment with a diverse team that enjoys working together
  • Many perks & benefits as well as a great office in the heart of Munich
  • A competitive salary plus a virtual stock option package

Auf diese Stelle bewerben

About Us

Working at Avelios means having a direct impact on improving our healthcare system and the quality of patient care. Our software is being used by doctors and nurses to treat patients in the best hospitals in Germany. We are growing fast and want to keep expanding our team and business to fundamentally digitize healthcare for the better. We appreciate different backgrounds and see diversity as one of our strengths.

Are you a talented, ambitious and impact-driven individual who wants to make a difference? Then what are you waiting for, apply now and join our team!

Auf diese Stelle bewerben

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