Meta
Research Engineer - AI Trust - Meta Superintelligence Labs
Menlo Park, CA
Sponsorship not specifiedDetected 74 days ago
PythonMachine LearningPyTorchNLPComputer VisionLLMsResearch
About the role
- Meta is seeking Research Engineers to join the Safety System and Foundations team within Meta Superintelligence Labs, dedicated to advancing the safe development and deployment of Superintelligent AI.
Responsibilities
- 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
- Build scalable infrastructure and tools for safety evaluation, monitoring, and rapid mitigation of emerging risks
- Work closely with researchers, engineers, and cross-functional partners to integrate safety solutions into Meta's products and services
- Lead complex technical projects end-to-end
- Experience as a technical lead on a team and/or leading complex technical projects from end-to-end
- Experience developing, fine-tuning, or evaluating LLMs across multiple languages and capabilities (text, image, voice, video, reasoning, etc)
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Programming experience in Python and hands-on experience with frameworks such as PyTorch Hands-on experience applying state-of-the-art techniques to build robust AI system solutions for safety and policy adherence
- Experience with distributed training of LLMs (hundreds/thousands of GPUs), scalable safety mitigations, and automation of safety tooling
Benefits
- PhD in Computer Science, Machine Learning, or a relevant technical field
- 3+ years of industry research experience in LLM/NLP, computer vision, or related AI/ML model training
Company info
- Our mission is to pioneer robust and foundational safety techniques that empower Meta's AI capabilities, ensuring billions of users experience our products and services securely and responsibly.
This listing is sourced directly from Meta's careers page and normalized into a canonical job model.