Key skills
Large Language Models (LLMs)Reinforcement Learning from Human Feedback (RLHF)Reinforcement Learning with Value Replay (RLVR)Proximal Policy Optimization (PPO)Generalized Proximal Policy Optimization (GRPO)Machine Learning ResearchAlgorithm DevelopmentAgent-based SystemsAIMachine Learning
About this role
Scale AI is a leading AI data foundry focused on accelerating the development of AI applications. The Machine Learning Research Engineer will work on applying agent reinforcement learning algorithms to enterprise datasets, creating best-in-class agents that achieve state-of-the-art results.
Responsibilities:
- Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers
- Research cutting edge algorithms to integrate directly into our training stack
- Build agents that leverage our proprietary agent-building algorithms to automatically hill climb datasets – including defining highly performant tools, multi-agent systems, and complex rewards
Requirements:
- 1-3 years of building with LLMs in a production environment
- Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc
- Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
- PhD or Masters in Computer Science or a related field