Remote AI Data Architect for Scalable Healthcare ML

Entrada; Polska; Remote; PLN 180,000 - 360,000; Full time

Benefits offered by this job

Remote work from Poland

MacBook provided

Referral bonus

Certification support

Leadership opportunities with Databrm

Job summary

Entrada AI is hiring a Data Architect to lead end-to-end AI lifecycles for global healthcare clients, building scalable ML systems on the Databricks Lakehouse. You will blend deep learning with data engineering and consultant skills to guide regulatory compliance and strategic AI decisions.

You will design robust pipelines, implement MLOps, and enable scalable model serving while collaborating with stakeholders to maximize clinical impact and governance across platforms.

Qualifications

• 5+ years in ML or data science with hands-on deployment in Databricks.
• Experience with medical imaging formats (DICOM, NIfTI).
• Strong Python and PySpark skills; SQL proficiency.
• Cloud experience (Azure or AWS) and GPU management.
• Experience with ML lifecycle tools (MLflow) and Delta Lake.

Responsibilities

• Design end-to-end AI lifecycles for healthcare clients and production-grade ML systems.
• Build scalable computer vision pipelines using PyTorch/TensorFlow on Databricks.
• Lead MLOps workflows, model versioning, and serving with MLflow and Model Serving.
• Ensure governance, security, and regulatory compliance in pipelines.
• Advise clients on build vs. buy and communicate value to stakeholders.
• Promote CI/CD for ML and use of Feature Stores for consistency.

Skills

Python

SQL

PySpark

MLflow

Delta Lake

Databricks

Azure/AWS

CNN/Transformers

English (C1+)

Education

Master's degree in Computer Science

Tools

MONAI

SimpleITK

OpenCV

Databricks Model Serving

Job description

Entrada AI is hiring a Data Architect to lead end-to-end AI lifecycles for global healthcare clients, building scalable ML systems on the Databricks Lakehouse. You will blend deep learning with data engineering and consultant skills to guide regulatory compliance and strategic AI decisions.

You will design robust pipelines, implement MLOps, and enable scalable model serving while collaborating with stakeholders to maximize clinical impact and governance across platforms.