About Usono
Usono is a MedTech company that revolutionizes musculoskeletal (MSK) ultrasound through dynamic imaging solutions. Our main product, ProbeFix Dynamic, is used by doctors of elite sports organizations such as Red Bull Salzburg, Lugano FC and research institutions such as Mayo Clinic & MIT. Thanks to our hardware, they unlock new insights in the body in movement, for prevention, diagnosis and rehabilitation.
We are seeking a hands-on and experienced Machine Learning Engineer to join our dedicated development team. As Machine Learning Engineer you are responsible for developing, validating, and deploying AI-driven algorithms that enhance the analysis, interpretation, and clinical usability of medical images. This role bridges advanced machine learning techniques with deep domain knowledge of medical imaging modalities (strong focus on Ultrasound) to support improved diagnostic accuracy, workflow efficiency, and patient outcomes. You will collaborate closely with software engineers, data scientists and designers (UI/UX/Visual) to deliver user-friendly and robust software products centered around medical imaging.
The Job
As our Machine Learning Engineer, you will work closely with the CTO and the data science and development team to further develop the AI model and software proposition. You’ll shape the future of dynamic ultrasound by:
- Contributing to a vision to build and expand Usono’s AI model
- Algorithm Research & Development: design, train, and optimize machine learning and deep learning models for tasks related to analyzing medical images.
- Determine ML strategy and methodologies: considering the data (availability), training, validation, generalization, robustness, (regulatory) compliance and deployment.
- Optimization of ML-ops: manage training and results consistently and traceable (in ClearML).
- Pre- and postprocessing (imaging) data: processing of imaging data and outcome data of model (e.g., DICOM handling, normalization, augmentation, artifact correction).
- Contributing to data management and quality: build pipelines for large-scale dataset processing, ensuring compliance with medical data standards and ensure privacy and ethical use of patient data, complying with HIPAA / GDPR regulations.
- Ensure deployment & integration: translate research models into production‑ready pipelines, collaborate with software engineers to integrate the model / artefacts in a cloud environment (AWS), monitor and maintain performance post deployment.
- Working closely with key stakeholders and partners
Who You Are
We’re looking for a machine learning with strong communication skills.
- MSc or PhD in Computer Science, Biomedical Engineering, Medical Imaging, Artificial Intelligence, or related field.
- Extensive experience (> 5 years) in Machine learning, including hands-on experience with various relevant frameworks (e.g. PyTorch / Tensorflow), and tools (e.g. ClearML, GitHub, Jira).
- Excellent skills in Python.
- Deep understanding of Machine Learning principles and best practices.
- Understanding of Medical Imaging Data and related constraints.
- Preferably understanding of and/or experience with Speckle Tracking and Optical Flow related models.
- Preferably understanding of medical grade software development, and familiarity with the relevant regulatory standards (MDR, FDA and ISO13485, IEC62304 of IEC82304)
- Understanding of and familiarity with relevant regulatory standards regarding privacy and security (e.g. GSPR, ISO27001)
What We Offer
- A key role in a fast-growing and internationally operating start-up company.
- Flexible in hybrid working, partially on High Tech Campus, partially from home
- Potential to participate in equity through SARs (details to be communicated in later interview stage).
- A chance to shape the future of medical ultrasound in elite sports and rehabilitation.
Ready to Make an Impact?
If you’re passionate about innovation in medical technology and want to help shape the future of dynamic ultrasound, we’d love to hear from you, so apply below 📩! If possible, add any relevant work or portfolio you might have.