<p>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. Our mission is to pioneer robust and foundational safety techniques that empower Meta's most ambitious AI capabilities, ensuring billions of users experience our products and services securely and responsibly.</p> <p>Minimum Qualifications</p> <ul> <li>Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience </li><li>PhD in Computer Science, Machine Learning, or a relevant technical field </li><li>3+ years of industry research experience in LLM/NLP, computer vision, or related AI/ML model training </li><li>Experience as a technical lead on a team and/or leading complex technical projects from end-to-end </li><li>Publications at peer-reviewed conferences (e.g. ICLR, NeurIPS, ICML, KDD, CVPR, ICCV, ACL) </li><li>Programming experience in Python and hands-on experience with frameworks such as PyTorch </li></ul> <p>Preferred Qualifications</p> <ul> <li>Hands-on experience applying state-of-the-art techniques to build robust AI system solutions for safety and policy adherence </li><li>Experience developing, fine-tuning, or evaluating LLMs across multiple languages and capabilities (text, image, voice, video, reasoning, etc) </li><li>Demonstrated experience to innovate in safety foundational research, including custom guideline enforcement, dynamic policy adaptation, and rapid hotfixing of model vulnerabilities </li><li>Experience designing, curating, and evaluating safety datasets, including adversarial and borderline prompt cases </li><li>Experience with distributed training of LLMs (hundreds/thousands of GPUs), scalable safety mitigations, and automation of safety tooling </li></ul> <p>Responsibilities</p> <ul> <li>Design, implement, and evaluate novel, systemic, and foundational safety techniques for large language models and multimodal AI systems </li><li>Create, curate, and analyze high-quality datasets for safety system and foundations </li><li>Fine-tune and evaluate LLMs to adhere to Meta's safety policies and evolving global standards </li><li>Build scalable infrastructure and tools for safety evaluation, monitoring, and rapid mitigation of emerging risks </li><li>Work closely with researchers, engineers, and cross-functional partners to integrate safety solutions into Meta's products and services </li><li>Lead complex technical projects end-to-end </li></ul> <p>About Meta</p> <p>Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.</p> <p>Equal Employment Opportunity</p> <p>Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.</p> <p>Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.</p>