Staff Machine Learning Engineer, Oncology Foundation Model
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Die Stelle
Architect, build, and maintain the data infrastructure powering large multimodal foundation models in healthcare.
Design end-to-end pipelines to ingest, process, and curate TB-scale heterogeneous data (genomics, pathology images, radiology, clinical notes) and integrate diverse knowledge sources.
Develop and optimize data loading and streaming frameworks (Hugging Face Datasets, MosaicML Streaming, Ray Data) and connect to knowledge graphs and biomedical repositories.
Collaborate with platform and infrastructure teams to leverage GCP services, ensuring performance, security, and cost efficiency.
Establish robust data monitoring, quality assurance, drift detection, and observability, with data lineage and alerting for reliable training and deployment.
Lead, mentor, and partner with researchers, engineers, clinicians, and product teams to translate data strategy into impactful patient-centered outcomes.
Design end-to-end pipelines to ingest, process, and curate TB-scale heterogeneous data (genomics, pathology images, radiology, clinical notes) and integrate diverse knowledge sources.
Develop and optimize data loading and streaming frameworks (Hugging Face Datasets, MosaicML Streaming, Ray Data) and connect to knowledge graphs and biomedical repositories.
Collaborate with platform and infrastructure teams to leverage GCP services, ensuring performance, security, and cost efficiency.
Establish robust data monitoring, quality assurance, drift detection, and observability, with data lineage and alerting for reliable training and deployment.
Lead, mentor, and partner with researchers, engineers, clinicians, and product teams to translate data strategy into impactful patient-centered outcomes.
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