We are seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Code Generation and LLMs reasoning with specific focus on reinforcement learning, synthetic data generation and advanced scaffolding/agentic techniques. You will have the opportunity to work with a broad and highly interdisciplinary team of scientists, engineers, and cross-functional partners, and will have access to cutting edge technology, resources, and research facilities.
AI Research Scientist Responsibilities
Lead, collaborate, and execute on research that pushes forward the state of the art in agentic code generation
Work towards long-term ambitious research goals, while identifying intermediate milestones
Directly contribute to experiments, including designing experimental details, implement reusable code, running evaluations, and organizing results
Contribute to publications and open-sourcing efforts
Mentor other team members. Play a significant role in healthy cross-functional collaboration.
AI Research Scientist Responsibilities
Lead, collaborate, and execute on research that pushes forward the state of the art in agentic code generation
Work towards long-term ambitious research goals, while identifying intermediate milestones
Directly contribute to experiments, including designing experimental details, implement reusable code, running evaluations, and organizing results
Contribute to publications and open-sourcing efforts
Mentor other team members. Play a significant role in healthy cross-functional collaboration.
Requirements:
Minimum Qualifications
Currently has or is in the process of obtaining a PhD in the field of Computer Science, Mathematics, or similar quantitative field
First-author publications at peer-reviewed AI conferences (e.g. NeurIPS, ICML, ICLR)
Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use
Experience working with SOTA RL codebases and familiarity with one or more deep learning frameworks (e.g. pytorch, VERL, )
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
Interested in real-world code generation and AI for software engineering
Enthusiastic about world models.
Minimum Qualifications
Currently has or is in the process of obtaining a PhD in the field of Computer Science, Mathematics, or similar quantitative field
First-author publications at peer-reviewed AI conferences (e.g. NeurIPS, ICML, ICLR)
Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use
Experience working with SOTA RL codebases and familiarity with one or more deep learning frameworks (e.g. pytorch, VERL, )
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
Interested in real-world code generation and AI for software engineering
Enthusiastic about world models.
This position is open to all candidates.
