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Research Engineer - Multimodal Embodiment Trust

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Meta

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Location:
United States , Menlo Park, CA

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

257000.00 USD / Year ▼
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Job Description:

Meta is seeking Research Engineers to join the Multimodal Embodiment Trust team within Meta Superintelligence Labs, dedicated to advancing the safe development and deployment of Superintelligent AI. Product & Applied Research group is focused on building AI-powered experiences for people, bringing frontier models to consumers. Our two primary goals are: to build a superintelligent personal sidekick that billions of people use to make their lives better; and to provide fresh, personal, insightful entertainment by allowing people to make, share, and consume AI-generated media and immersive experiences.

Job Responsibility:

  • Design, implement, and evaluate novel, systemic, and foundational safety techniques for large language models and multimodal AI systems
  • Create, curate, and analyze high-quality datasets for safety system and foundations
  • Fine-tune and evaluate LLMs to adhere to Meta’s safety policies and evolving global standards
  • Contribute to applied research through risk analysis, experimentation, measurement, and and building mitigations
  • Work closely with researchers, engineers, and cross-functional partners to integrate safety solutions into Meta’s products and services

Requirements:

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • PhD in Computer Science, Machine Learning, or a relevant technical field
  • Experience in LLM/NLP, computer vision, or related AI/ML model training
  • End-to-end experience working on complex technical projects
  • Publications at peer-reviewed conferences (e.g. ICLR, NeurIPS, ICML, KDD, CVPR, ICCV, ACL)
  • Programming experience in Python and hands-on experience with frameworks such as PyTorch

Nice to have:

  • Hands-on experience applying state-of-the-art techniques to build robust AI system solutions for safety and policy adherence
  • Experience developing, fine-tuning, or evaluating LLMs across multiple languages and modalities (text, image, voice, video, reasoning, etc)
  • Demonstrated experience to innovate in safety foundational research, including custom guideline enforcement, dynamic policy adaptation, and rapid hotfixing of model vulnerabilities
  • Experience designing, curating, and evaluating safety datasets, including adversarial and borderline prompt cases
  • Experience with distributed training of LLMs (hundreds/thousands of GPUs), scalable safety mitigations, and automation of safety tooling
What we offer:
  • bonus
  • equity
  • benefits

Additional Information:

Job Posted:
February 13, 2026

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