Databricks Data Architect (Healthcare & Life Sciences)

Entrada AI is a specialized consulting partner and a strategic portfolio company of Databricks Ventures. They focus on deploying Databricks Genie at enterprise scale and have delivered over 150 Databricks projects unlocking self-service analytics for Fortune 500 leaders.

• 5+ years in Machine Learning or Data Science, with at least 3 years deploying models within the Databricks ecosystem.
• Proven experience handling medical imaging formats (DICOM, NIfTI, WSI) and familiarity with libraries such as MONAI, SimpleITK, or OpenCV.
• Advanced proficiency in Python (PyData stack) and SQL; experience with PySpark for large-scale data manipulation.
• Production experience in Azure (Azure Machine Learning, ADLS Gen2) or AWS (SageMaker, S3), focusing on GPU instance management and cost optimization.
• Expertise in MLflow for the full ML lifecycle and experience with Delta Lake and Databricks Model Serving or TorchServe.
• Strong understanding of deep learning architectures (CNNs, Transformers, SegNet) and evaluation metrics for medical diagnostics.
• Fluent English (C1+) for client collaboration and ability to explain complex algorithms to non-technical stakeholders.
• Commitment to technical excellence, ideally with certifications such as Databricks Machine Learning Professional or specialized cloud AI certifications.

• Design and implement scalable computer vision pipelines using PyTorch or TensorFlow, leveraging Databricks Runtime for ML to process large-scale medical imaging datasets (DICOM, NIfTI).
• Architect end-to-end MLOps workflows using MLflow for experiment tracking, model versioning, and production-grade Model Serving.
• Develop efficient data loaders and preprocessing steps for high-dimensional medical data, utilizing Apache Spark to parallelize image transformation and feature extraction.
• Enforce data lineage and security protocols via Unity Catalog, ensuring compliance with healthcare regulatory standards (HIPAA/GDPR/HITRUST).
• Advise clients on building vs. buying medical AI tools and share best practices on model interpretability and bias mitigation in clinical settings.
• Implement CI/CD for ML (Git integration, Databricks Asset Bundles) and promote the use of Feature Stores to ensure consistency between training and real-time inference.

By applying, candidates consent to data processing for recruitment. The data controller is ENTRADA AI Sp. z o.o. based in Kraków, Poland.