Senior MLOps Engineer — Healthcare Platform (Hybrid)

United States Digital Space LLC; Paris; Hybride; EUR 90 000 - 150 000; Plein temps

Avantages offerts par ce poste

Hybrid work setup (up to 2 remote days

Health insurance

Lunch vouchers (Swile card)

Résumé du poste

United States Digital Space LLC is seeking a Senior MLOps Engineer for its ML Platform team in Paris. You will build and scale infrastructure to deploy ML models across Europe, collaborating with data scientists and engineers to deliver reliable AI solutions for care teams and patients.

Key responsibilities include designing the MLOps pipeline, maintaining tooling, and promoting best practices across the tech org.

Qualifications

• Proficient in Python, SQL, Shell Scripting, and Terraform; containerize ML pipelines with Docker.
• Strong knowledge of cloud platforms, especially AWS SageMaker, EC2, ECS, S3, CloudWatch.
• Experience with ML frameworks, preferably PyTorch, and HuggingFace tools.
• Familiar with Kubernetes, GitOps (ArgoCD), Kafka, and model deployment workflows.
• Excellent written/spoken English and cross-functional collaboration.

Responsabilités

• Build and deploy production-grade ML models with data scientists and engineers.
• Design and maintain the MLOps pipeline, including CI/CD and monitoring of models.
• Develop tools, frameworks, and best practices for end-to-end ML lifecycle.
• Ensure availability and performance of ML systems; proactively resolve issues.
• Collaborate with cross-functional teams to gather requirements and guide solutions.
• Share MLOps knowledge through documentation and internal knowledge transfer.

Connaissances

Fluent English

Cross-functional collaboration

Communication

Proactive learning

Outils

Python

SQL

Shell Scripting

Terraform

Docker

Kubernetes

ArgoCD

Kafka

PyTorch

HuggingFace Transformers

Accelerate

PEFT

transformers.js

langchain.js

Description du poste

United States Digital Space LLC is seeking a Senior MLOps Engineer for its ML Platform team in Paris. You will build and scale infrastructure to deploy ML models across Europe, collaborating with data scientists and engineers to deliver reliable AI solutions for care teams and patients.

Key responsibilities include designing the MLOps pipeline, maintaining tooling, and promoting best practices across the tech org.