Research Engineer, FAIR SGT - Paris

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

Job summary

Meta's FAIR organization is seeking a Research Engineer in Paris to drive advancements in generative models, focusing on data efficiency and continual learning in large language models. The role spans research, engineering, and deployment for both product and frontier model efforts.

You will lead experiments, implement reusable code, and contribute to publications and open-source initiatives while mentoring teammates.

Qualifications

• Experience training and fine-tuning foundation models beyond black-box usage.
• Familiarity with PyTorch.
• Must be able to obtain work authorization in France.

Responsibilities

• Lead and execute research to advance state-of-the-art generative models.
• Systematically perform independent research and adapt to new developments.
• 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.

Skills

PyTorch

Foundation models

Job description

Summary:

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.

Required Skills:

Research Engineer, FAIR SGT - Paris Responsibilities:

1. Lead and execute research to advance the state-of-the-art in generative models and LLM performance

2. Systematically perform independent research, quickly adapting to new developments in the field

3. Directly contribute to the experimental process, including designing details, implementing reusable code, running evaluations, and organizing results

4. Contribute to publications, open-sourcing initiatives, and mentor other team members

5. Ensure effective cross-functional collaboration

Minimum Qualifications:

Minimum Qualifications:

1. Demonstrated experience with training, fine-tuning, and experimentation on foundation models beyond black-box usage

2. Familiarity with PyTorch

3. Must be able to obtain and maintain work authorization in the country of employment

Preferred Qualifications:

Preferred Qualifications:

1. Ability to conduct independent research, communicate complex ideas with peers

2. Hold first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR)

Industry: Internet