Raidium develops a new generation of radiological copilot, based on Raidium’s custom-trained Foundation Model. This copilot is a webapp (react + FastAPI) that interacts with the ML Model (Pytorch on GPU).
As Full-stack Software engineer at Raidium, play a pivotal role in developing the Raidium product and integrating Machine Learning models.
Design, implement, and maintain both front-end and back-end components of Raidium product, involving serving ML models and manipulating radiological images
Collaborate with ML Engineers to integrate advanced ML/Deep Learning models into the platform, ensuring the system is highly accurate and efficient.
Build the infrastructure and pipelines to support rapid growth in users and data volume without compromising performance.
Enforce the best practices to ensure code quality and system soundness: automatic testing, linting, typing,…
Master’s degree in Computer Science, Engineering, or a related field.
Proficient in full-stack development, with experience in modern programming languages (e.g., Python, JavaScript), frameworks (e.g., FastAPI, React) and databases systems.
Willingness to work in the healthcare industry
Authorization to work in France
Fluency in English, with excellent communication and teamwork skills
Willing to come to the office (2 days remote policy)
Experience in an agile work environment
Knowledge of machine learning concepts and experience integrating ML models
Experience with containerization and orchestration tools such as Docker and Kubernetes
Experience with cloud providers (GCP, AWS, Azure)
Knowledge of model serving technologies (ex: ray, CUDA)) and parallelization on GPU clusters
Experience with Radiological images (DICOM, nifti)
Have a real and positive impact on people’s lives
Apply and improve the latest Deep Learning technologies to build an inspiring product
Be in contact with radiologists in our partner center
Work with a team of internationally recognized experts
Work with a diverse team of engineers and medical doctors
Competitive salary
Access to premium computing hardware
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