Partner with product teams to define requirements and drive quality and deliveryA strong ML background with hands-on experience training models, and a record of results shown through publications (e.g., ACL, CHI, CVPR, EMNLP, FAccT, ICML, Interspeech, NeurIPS, UIST) or other clear evidence of impact Strong coding skills, including the ability to work with messy, real-world codebases If not already experienced with LLMs, must be able to quickly pick up the skills needed for safety post-training Strong collaboration and communication skills Willingness to work with sensitive content, including exposure to offensive or controversial materialBS, MS, or PhD in Computer Science, Machine Learning, or a related field, or equivalent experience Direct experience with LLMs and post-training methods, including safety alignment Experience in one or more of: agentic safety (tool use, multi-step agents), model character and persona design, or multimodal safety (audio and vision) Strong organizational skills and experience working across large, diverse teams. Our team focuses on the research and methods needed to make large language models safe, fair, and robust at scale, with a current focus on agentic safety, model character and persona, and multimodal safety across audio and vision.