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Staff Machine Learning Engineer, Oncology Foundation Model
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The role
Lead the design, build, and operation of the data infrastructure powering large multimodal foundation models.
Architect scalable data ingestion and processing pipelines for heterogeneous biomedical data (genomics, pathology, radiology, and clinical notes) optimized for GPU-based training.
Develop and optimize data loading, streaming, and knowledge integration using frameworks like Hugging Face Datasets, MosaicML Streaming, and Ray.
Collaborate with platform, research, and clinical teams to implement compliant, cost-efficient cloud-native data solutions on GCP.
Establish robust data quality, drift detection, monitoring, and alerting; manage data I/O bottlenecks and pipeline reliability.
Provide technical leadership, mentorship, and a bias-to-action approach to deliver rapid, measurable improvements in healthcare AI.
Architect scalable data ingestion and processing pipelines for heterogeneous biomedical data (genomics, pathology, radiology, and clinical notes) optimized for GPU-based training.
Develop and optimize data loading, streaming, and knowledge integration using frameworks like Hugging Face Datasets, MosaicML Streaming, and Ray.
Collaborate with platform, research, and clinical teams to implement compliant, cost-efficient cloud-native data solutions on GCP.
Establish robust data quality, drift detection, monitoring, and alerting; manage data I/O bottlenecks and pipeline reliability.
Provide technical leadership, mentorship, and a bias-to-action approach to deliver rapid, measurable improvements in healthcare AI.
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