Machine Learning Engineer at FUSE-AI

As a young and dynamic eHealth company, FUSE-AI pursues the goal of improving medical care with innovative AI-based software products.

Develop, produce and improve computer vision models for image classification, segmentation, and image analysis using Deep Learning and classical image analysis techniques.
Planning, design and implementation of machine learning systems and integration into software products or projects based on TensorFlow, Keras, Python.
Conduct feasibility analyses of problems regarding artificial intelligence and machine learning and develop suitable solution strategies.
Support in the selection and integration of suitable tools, frameworks and technologies to improve ML development and deployment processes according to regulatory compliance.
Further development and optimization of products and monitoring/maintenance systems.
Analyze and solve complex development tasks in teamwork.
Independent study of state of the art knowledge.

Proficiency in Python and object-oriented software programming (e.g. C++).
Ability in other programming languages (e.g. Java, Go or Rust) is a plus.
Proficiency in CNNs and machine learning in the medical field.
Competent in troubleshooting (e.g. hotfixes).
Proficiency in software engineering in collaboration with Git.
Competent in requirement engineering regarding usability and clinical indication.
Competent in agile project development methodologies and project management (e.g. Jira, MS Project).
Competent in monitoring, maintenance and change control of software development in a regulated field.
Competent in versioning, data logging and their visualization.
Know-how for systematic researching of machine- and especially deep-learning algorithms.
Configuration and managing databases such as MySQL, MongoDB.
Competent in concepts for software development procedures.
Knowledge with medical device regulations (EU MDR, FDA, ISO).
Experience in medical image processing projects, AI projects in medicine and other AI-based developments.