Data Engineer

Moonlight Ai GmbH; Basel; Hybrid; CHF 120.000 - 170.000; Vollzeit

Zusammenfassung

Moonlight Ai GmbH in Basel is seeking a Data Engineer to build core data, ML, and deployment infrastructure for scalable, traceable clinical diagnostics systems. You will work across data engineering, MLOps, and ML platform development in a regulated environment to ensure data digitization quality from ingestion to inference.

Responsibilities include building ingestion pipelines for multi-modal datasets, collaborating on data warehouse quality, enabling model training, evaluation, deployment,

Qualifikationen

• 4+ years building scalable pipelines for large-scale structured and unstructured data.
• Experience with Infrastructure-as-Code (IaC) e.g. Terraform, CloudFormation.
• Experience with distributed or high-performance data processing with reproducible, version-controlled infrastructure.
• 2+ years developing data or ML systems in a regulated environment with reproducibility, auditability, and data governance.
• Fluent in Python and familiar with PyTorch or TensorFlow.
• Effective communication (English) and interpersonal skills.
• Valid work permit in Switzerland or EU and availability to travel to Tunisia.
• Exposure to ISO 27001 / ISO 13485 is a plus.
• Exposure to Software as a Medical Device (SaMD) or clinical integrations is a strong plus.

Aufgaben

• Build robust data ingestion pipelines for multi-modal datasets consisting of gigapixel images paired with genomic results and clinical metadata.
• Together with the Software Engineer, design unit testing, logging, and controls for a complete data warehouse spanning structured and unstructured data.
• Ensure data quality, consistency, and traceability by authoring the ML platform for training, evaluation, deployment, and monitoring.
• Develop FDA- and IVDR-compliant frameworks for dataset access control, model versioning, and experiment tracking.
• Innovate on existing image processing methods in collaboration with ML Engineers.
• Develop containerized, production-grade services for model inference in on-prem, cloud, or OEM contexts.

Kenntnisse

Data pipelines

MLOps

Data modeling

Experiment tracking

Python

English communication

Tools

Terraform

CloudFormation

Jobbeschreibung

As a Data Engineer, you will build and implement the core data, ML, and deployment infrastructure that enables scalable, reproducible, and traceable machine learning systems for use in clinical diagnostics. In addition, your code will ensure the traceability and quality of all digitized data from ingestion to research, model development, clinical validation, and inference. This high-impact role spans data engineering, MLOps, and ML platform development in a regulated environment.

Responsibilities:

Build robust data ingestion pipelines for multi-modal datasets consisting of gigapixel images paired with genomic results and clinical metadata

Together with the Software Engineer, design unit testing, logging, and controls to ensure a high-quality and complete data warehouse spanning structured and unstructured data

Ensure data quality, consistency, and traceability by authoring the ML platform that enables training, evaluation, deployment, and monitoring of ML models

Develop FDA- and IVDR-compliant frameworks for dataset access control, model versioning, and experiment tracking that align with regulatory strategy and jurisdictional requirements

Innovate on existing image processing methods, in collaboration with our ML Engineers

Develop containerized, production-grade services for model inference in an on-premises, cloud computing, or OEM-integrated context.

Requirements:

4+ years of experience:

Building scalable pipelines for large-scale structured and unstructured data, using Infrastructure-as-Code (IaC) e.g. Terraform, Cloudformation, etc.

Building solutions for distributed or high-performance data processing with reproducible, version-controlled infrastructure

Experience with data modeling, distributed or high-performance data processing, experiment tracking, and MLOps in a production environment

2+ years experience developing data or ML systems, preferably in a regulated environment (e.g. medical devices, healthcare, financial services) with an understanding of requirements such as reproducibility, auditability, and data governance

Fluent in python and familiar with at least one deep learning framework (e.g. PyTorch, TensorFlow)

Effective communication (English) and interpersonal skills.

Valid work permit in Switzerland or EU and availability to travel to Tunisia.

Exposure to ISO 27001 / ISO 13485 a plus

Exposure to Software as a Medical Device (SaMD) or clinical integrations is a strong plus