(Junior) Machine Learning Engineer (all)

About The Role

As a (Junior) Machine Learning Engineer, you’ll be part of our AI team developing deep learning models for real-world medical applications. Your focus will be on building and validating ML solutions that analyze radiological imaging data (MRI, CT) to support accurate and efficient diagnoses. You’ll work hands-on with modern deep learning frameworks (e.g. PyTorch), contribute to model training and evaluation, and ensure the models meet clinical and regulatory standards. In this role, you'll gain valuable experience in medical AI development—from experimentation and data handling to deployment within a certified software product.

This is a great opportunity if you’re early in your career and eager to grow in a highly impactful domain at the intersection of machine learning and healthcare.

Your Responsibilities

• Develop and train deep learning models to detect and diagnose medical conditions from radiological imaging data (MRI, CT).
• Rigorously validate model performance to assess product-market fit and ensure compliance with medical device certification standards.
• Build solutions with clinical needs in mind — placing strong emphasis on interpretability and confidence estimation, which are essential in healthcare settings.
• Work within a modern software environment powered by Docker and AWS, enabling scalable and efficient model development and deployment.

Your Background

• Experience in computer vision, gained in industry or Master’s/ Ph.D. in Engineering, Computer Science, Machine Learning, Mathematics, Statistics, or a related field.
• Strong understanding of machine learning and deep learning concepts — you know how to design meaningful experiments and perform rigorous statistical analysis.
• Hands-on experience with deep learning frameworks, ideally PyTorch.
• Familiarity with one or more of the following areas:
• Proficient in Python; experience with C/C++ is a plus.
• Confident in working with large and diverse datasets from various sources and formats.
• Solid software engineering practices: version control, unit testing, continuous integration, and a commitment to clean, maintainable code
• Convolutional Neural Networks (2D and 3D)
• Semantic segmentation
• Object detection
• Medical image processing

NICE TO HAVE

• Background in medical imaging.
• Publications at top-tier conferences or in peer-reviewed journals.
• Experience with Docker and cloud platforms like AWS.
• Familiarity with relational and non-relational databases.

What You Can Expect

• Fokus auf das, was zählt: Bei uns sind Kompetenz, Persönlichkeit und Engagement wichtiger als Formalitäten oder der Studiengang, den du gewählt hast.
• Dein Einfluss: Mit deiner Arbeit trägst du dazu bei, die Diagnose von Krankheiten schneller, präziser und besser beherrschbar zu machen.
• Dein Team: Werde Teil eines hochmotivierten, interdisziplinären Teams mit schnellen Entscheidungsprozessen und einer kollaborativen Atmosphäre.
• Gestaltungsspielraum: Arbeite remote oder in unserem Büro in Berlin-Kreuzberg – ganz nach deinen Vorlieben.
• Benefits: Setze dein persönliches Benefits-Budget flexibel ein und wähle die Vorteile, die am besten zu dir passen!