Senior Foundation ML Engineer - Production Pipelines, Remote

AZmed; Paris; Hybride; EUR 90 000 - 120 000; Plein temps

Avantages offerts par ce poste

Meal vouchers

BSPCE

Résumé du poste

AZmed in Paris is seeking a Machine Learning Engineer to bridge experimental research and production systems, empowering AI researchers to scale and deploy cutting-edge technologies. The role focuses on maintaining data and model quality, owning the AI codebase, and raising engineering standards across the team.

You will optimize the Foundation Model pipeline, drive AI feature development, and collaborate with Ops, MLOps and Software Engineering to ensure reliable infrastructure and rapid

Qualifications

• Master’s degree in statistics, data science, AI or related field.
• 5+ years of experience as a data engineer or data scientist in ML.
• Experience with medical images and ML applications.
• Experience training or fine-tuning foundation models.
• Experience with image-text alignment, VLM, and LLaVA.

Responsabilités

• Bridge research and production teams to deploy ML models.
• Maintain quality and evolution of datasets and models.
• Own AI team codebase and enforce standards via PRs.
• Optimize Foundation Model pipeline and data prep.
• Collaborate with Ops, MLOps, and Dev teams for reliability.
• Drive AI feature development and streamline release pipelines.
• Reduce time to production for AI models and operating points.

Connaissances

ML stack

Computer Vision

NLP

Data Engineering

Proactive

Ownership

Formation

Master’s degree in statistics, data science, AI

Outils

pytorch

sklearn

skimage

Mongodb

SQL

Spark

Airflow

dvc

Description du poste

AZmed in Paris is seeking a Machine Learning Engineer to bridge experimental research and production systems, empowering AI researchers to scale and deploy cutting-edge technologies. The role focuses on maintaining data and model quality, owning the AI codebase, and raising engineering standards across the team.

You will optimize the Foundation Model pipeline, drive AI feature development, and collaborate with Ops, MLOps and Software Engineering to ensure reliable infrastructure and rapid