Platform Engineer

RaySearch develops innovative software solutions to improve cancer care. Over 1200 clinics in more than 54 countries use RaySearch software to improve treatments and quality of life for patients. RaySearch was founded in 2000 and is listed on Nasdaq Stockholm. The headquarters is located in Stockholm, with subsidiaries in the US, Europe, Asia and Australia & New Zealand. Today we are more than 485 employees with a common vision of improving cancer care with innovative software. Our great staff is crucial for our success and we offer a fantastic working environment in modern offices, flexibility and good opportunities for development. We believe in equal opportunities, value diversity and work actively to prevent discrimination.RaySearch is expanding its machine learning capabilities and is looking for a Machine Learning Platform Engineer to join our headquarters in Stockholm. This is an office-first role. You will help build our model development platform: the systems that take clinical data through curation, training and validation to deployed models. Our deep learning models are used in RayStation, our treatment planning system, at cancer clinics worldwide. The platform you build is how the next generation of these models gets made. This is not primarily a model development role. Your focus is the platform, data and infrastructure that let ML engineers develop, validate and deploy models reliably. About the job You will join RaySearch's Machine Learning department and help build a platform that covers the full model lifecycle, from clinical data coming in to validated models going out. The work spans: Data curation and management: ingesting, organizing and validating large clinical datasets and medical images, with ETL, databases and storage that keep track of where data came from and how it was used. Model training: reproducible training pipelines orchestrated with Flyte, for dose prediction, segmentation, detection, classification and image registration, with monitoring of training runs. Validation: automated evaluation and reporting that connects data, method, code and results, including web-based tools for reviewing images, contours, radiotherapy plans and validation outcomes. Deployment and ML integration: getting models into production and integrated into our software products, including inference optimization. Operations: monitoring training and evaluation runs, keeping services and databases up to date, and troubleshooting when things go...

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