Manager, Research Scientist: Post-Training

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the progress of generative AI, with a focus around frontier evaluations, the science of data around posttraining, agentic applications, trustworthy agents oversight framework and beyond. 

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Manager of the LLM post-training Research team, you will lead a talented team of research scientists and research engineers focused on optimizing data curation and algorithmic improvements to enhance LLM capabilities in both text and multimodal modalities. 

In this role, you will manage a team of researchers developing novel methods to improve the alignment and generalization of large-scale generative models. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs. 

You will:

• Lead a team of highly effective research scientists and research engineers on LLM post-training  
• Develop novel post-training techniques to enhance LLM core capabilities in text and multimodal modeling.
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects
• Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
• Remain deeply involved in the research community, both understanding trends, and setting them
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.
• Must be able to commute to the San Francisco Office 4 times weekly. 

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience supporting and leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.