Forskningsingenjör inom maskininlärning och hälsodata
Core
Building and maintaining secure data pipelines (ETL) for large-scale pseudonymized health data and optimizing machine learning code for causal models and simulation tools.
Role type
Research Engineer (Machine Learning & Health Data)
Builds
Clinical decision support software interface and simulation tools (CARE-Sim) for primary care.
Domain
Healthcare / Artificial Intelligence / Data Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Python, Git, CI/CD, Docker, ETL pipeline construction, software integration
Preferred skills
Deep learning (PyTorch/TensorFlow), Transformer models, causal AI, handling electronic patient records, academic-clinical collaboration
Technologies
PyTorch, TensorFlow, TakeCare, VAL, LISA, CARE-Sim
Responsibilities
Build and maintain secure ETL pipelines for health data; optimize and scale machine learning code; develop and integrate clinical decision support software; provide technical support during clinical trials.
Seniority
Mid-level, hands-on IC