Research Scientist, AI, Formal and informal Reasoning

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Research Scientist, AI, Formal and informal Reasoning Paris, France Meta is seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in LLMs reasoning, using reinforcement learning, synthetic data generation and advanced scaffolding/agentic techniques, partially with a focus on formal and informal maths. 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, important resources, and research facilities. Responsibilities: - Lead, collaborate, and execute on research that pushes forward the state of the art in reasoning research, with an initial focus on formal and informal mathematical reasoning - Work towards long-term high-stakes 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 Minimum qualifications: - Holds a PhD in the field of Computer Science, Mathematics, or similar quantitative field - Experience training and evaluating large models on State-of-the-Art codebases and developing new architectures, losses and training recipes - 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 Reinforcement Learning codebases and familiarity with one or more Machine Learning frameworks (e.g. pytorch, VERL, …) - Must obtain work authorization in the country of employment

Read the full description at www.metacareers.com. FewerJobs shows a preview and links to the original posting.