AI Platform & MLOps Engineer (M/F)
Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Aug 27, 2026.
Contexte
Institute Curie is recruiting a Research Engineer) or Scientist in Artificial Intelligence (M/F) to join the AGORA project (AGentic Orchestration for Research and Clinical Applications in Oncology).
The ambition of AGORA is to design and validate one of the first agentic AI platforms fully dedicated to biomedical research and precision oncology. The platform will be capable of exploring complex biological data, integrating the latest medical knowledge, assisting molecular interpretation, and generating novel research hypotheses. To achieve this goal, AGORA combines large language models (LLMs), biomedical knowledge bases, bioinformatics tools, multi-omics datasets, and clinical data into a unified reasoning framework.
The project brings together experts in artificial intelligence, machine learning, and data science, specialists in health data integration and governance, researchers in systems biology and mechanistic modelling, as well as oncologists actively involved in precision medicine programmes.
The successful candidate will work at the interface of these different groups and will join the Bioinformatics Core Facility and INSERM U1331 Computational Oncology Unit, a highly interdisciplinary environment comprising approximately 100 researchers working in computational biology, bioinformatics, and artificial intelligence.
Main Responsabilities
The position is central to the project and aims to develop the scientific and technological foundations of a new generation of AI assistants for oncology.
As the main AI platform/MLOps engineer (M/F), you will:
· Design the core AI platform architecture and define standards best practices for the project.
· Develop production-ready AI services, APIs, and infrastructure supporting RAG and multi-agent workflows.
· Ensure reproducibility, lineage tracking, logging, auditing and traceability of AI workflows.
· Implement evaluation and continuous validation pipelines for LLM-based systems.
· Define and monitor operational, performance, quality and reliability metrics.
· Build and maintain observability frameworks for AI systems and LLM applications.
· Implement monitoring pipelines covering inference workloads, latency, availability, cost and user interactions.
· Contribute to deployment and operation of GPU and inference infrastructure.
· Work closely with the Institut Curie Data Office and IT teams to ensure compliance and security.