AI/ML Ops Engineer — Biologics Discovery

Johnson & Johnson Innovative Medicine; Beerse; Sur place; EUR 96 000 - 153 000; Plein temps

Résumé du poste

Johnson & Johnson Innovative Medicine is seeking a Senior ML Engineer for the Biologics Discovery Data Science team. You will deploy, monitor, and govern ML/AI solutions, enabling partner teams to run AI workflows reliably in discovery environments.

You will collaborate with data scientists and discovery scientists to operationalize model-ready data, ensure governance, and scale AI capabilities for biologics discovery with robust CI/CD and observability.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• 4+ years of experience operationalizing and scaling AI/ML solutions in production environments.
• Strong Python proficiency with AI/ML workflows for training, fine-tuning, evaluation, deployment, and serving.
• Experience with cloud infrastructure and modern data platforms for AI/ML workloads.
• Experience with model registries, experiment tracking, and ML lifecycle tools (e.g., MLflow, Weights & Biases).
• Experience implementing production AI/ML practices, including CI/CD, monitoring, containers, orchestration, and scalable compute.

Responsabilités

• Build and operate scalable pipelines delivering model-ready data to ML, generative AI, and agentic workflows.
• Enable closed-loop scientific learning by capturing and governing newly generated data for downstream modeling and evaluation.
• Establish reliable deployment, serving, monitoring, access control, and lifecycle management across environments.
• Implement versioning, reproducible releases, rollback capabilities, and traceability across the AI/ML lifecycle.

Description du poste

Johnson & Johnson Innovative Medicine is seeking a Senior ML Engineer for the Biologics Discovery Data Science team. You will deploy, monitor, and govern ML/AI solutions, enabling partner teams to run AI workflows reliably in discovery environments.

You will collaborate with data scientists and discovery scientists to operationalize model-ready data, ensure governance, and scale AI capabilities for biologics discovery with robust CI/CD and observability.