Senior Machine Learning Research Engineer (Deep Learning, Sensor Intelligence Group)

Master’s or PhD degree in either Computer Science, Electrical engineering, Biomedical engineering, Data Science, Artificial Intelligence, Statistics, or a related field

Must have published research papers in ML/DL domains, preferably application of ML/DL on biomedical data

Solid understanding of ML fundamentals, and particularly DL techniques. At the SIG team, we like to be aware of the mathematics behind the algorithms we use

4+ years of work/academic experience as a Machine-Learning/Deep-Learning researcher (2+ years, post-PhD work experience with those having a PhD degree). The requirements may be relaxed for exceptional candidates.

Experience developing or supporting regulated or high-risk ML systems (e.g., digital health, software as a medical devices), including familiarity with validation, documentation, and change-management requirements in regulated environments is a significant plus.

Strong experience with time series data, e.g. data pertaining to wearables, physiological signals or any high-frequency sensor data. Familiarity with signal processing concepts and techniques is expected.

Strong experience with multiple DL architectures is expected. Experience in training/fine-tuning/deploying Foundation AI models is a plus.

Proficiency in Python (scientific stack), ML/DL frameworks and libraries, e.g. PyTorch, TensorFlow.

Experience with cloud computing platforms (e.g. AWS or GCP) is a plus.

Strong communication (both written and oral) and collaboration skills across cross-functional teams.

Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions.

Demonstrated ability to think innovatively and adapt to changing requirements while consistently producing high-quality reports within tight deadlines.