Scale AI

Manager for a GenAI research team focused on evaluation, post-training, agents, and RL environments. The role involves leading a team, defining research roadmaps, driving execution, and collaborating cross-functionally. Requires a strong research background with publications and experience in fast-paced environments.

Scale AI is seeking a Staff Machine Learning Research Engineer focused on post-training algorithms for complex agents in enterprise GenAI applications. The role involves building a next-generation Agent RL training platform, integrating cutting-edge research, and training state-of-the-art models for enterprise customers, including cybersecurity and healthtech use cases. Experience with LLM training, post-training methods like RLHF/RLVR, and publications in top conferences are required.

Scale AI is seeking an ML Systems Research Engineer to work on building algorithms for their next-gen Agent RL training platform, supporting large-scale training, and researching/integrating state-of-the-art technologies to optimize ML systems. The role involves post-training state-of-the-art models for enterprise engagements and creating next-gen agent training algorithms for multi-agent/multi-tool rollouts.

This role focuses on researching and building synthetic data pipelines and agents to improve enterprise GenAI models. It involves creating agents for trace analysis, contributing to an agent-building framework, and training state-of-the-art models using post-training and agent-building algorithms.

Research Scientist focused on LLM post-training techniques (SFT, RLHF, reward modeling) to enhance text and multimodal capabilities. Involves optimizing data curation, analyzing model behavior, and publishing findings.

This role is for a Machine Learning Fellow focused on designing, evaluating, and interpreting advanced generative AI systems. The fellow will work on ML projects, contribute to research publications, and engage with a community of AI researchers. The role involves optimizing PyTorch models, evaluating ML code, advising on GPU optimization, and collaborating on research papers.

This role involves applying academic and professional expertise to design, evaluate, and interpret advanced generative AI systems. The fellow will work on ML projects, optimize PyTorch models, evaluate ML code, advise on GPU optimization, and contribute to research publications and technical reports.