Manager, Machine Learning Research Scientist, GenAI

Scale AI, Inc.•San Francisco, CA

33d

About The Position

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications. As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You'll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed. As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You'll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

Requirements

5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
Experience and track of recording in landing major research impacts in a fast-paced environment
Experience leading or managing research teams. You're excited to mentor, coach and develop talent.
Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.

Responsibilities

Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).
Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.
Stay deeply connected to the research community, understanding major trends, and helping set them.
Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.