Research Engineer, FAIR SGT - Paris

Meta; Paris; On-site; EUR 90,000 - 150,000; Full time

Job summary

Meta’s Fundamental AI Research (FAIR) group seeks a Research Engineer to push the boundaries of generative models and LLMs, spanning research, engineering, and deployment for product and frontier model efforts.

Key duties include leading experiments, building reusable code, and contributing to publications and open-source work, while mentoring teammates and collaborating across functions.

Qualifications

• Experience training, fine-tuning, and experimentation on foundation models beyond black-box usage.
• Ability to conduct independent research and communicate complex ideas with peers.
• First-author publications at NeurIPS/ICML/ICLR are preferred.

Responsibilities

• Lead and execute research to advance generative models and LLM performance.
• Design experiments, implement reusable code, run evaluations, and organize results.
• Contribute to publications, open-sourcing initiatives, and mentor other team members.
• Ensure effective cross-functional collaboration across research, engineering, and deployment.
• Work across product and frontier model efforts to drive impact.

Skills

Foundation models

Fine-tuning

Independent research

Publications

Tools

PyTorch

Job description

About

Meta's Fundamental AI Research (FAIR) organization is seeking a Research Engineer to drive advancements in generative models, with a particular focus on fundamental topics (data efficiency, continual learning) in large language models (LLMs) research. The role involves working across the full spectrum of research, engineering, and deployment for both product and frontier model efforts.

Responsibilities

• Lead and execute research to advance the state-of-the-art in generative models and LLM performance
• Systematically perform independent research, quickly adapting to new developments in the field
• Directly contribute to the experimental process, including designing details, implementing reusable code, running evaluations, and organizing results
• Contribute to publications, open-sourcing initiatives, and mentor other team members
• Ensure effective cross-functional collaboration

Minimum Qualifications

• Demonstrated experience with training, fine-tuning, and experimentation on foundation models beyond black-box usage
• Familiarity with PyTorch
• Must be able to obtain and maintain work authorization in the country of employment Ability to conduct independent research, communicate complex ideas with peers
• Hold first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR)