Machine Learning Systems Research Engineer, Agent… at Scale AI · NYC…

Summary: Scale AI is on a mission to accelerate the development of AI applications. As a Machine Learning Systems Research Engineer, you will build algorithms for next-gen Agent RL training platforms and collaborate with ML teams to enhance research and development. Responsibilities: - Build, profile and optimize our training and inference framework - Post-train state of the art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements - Collaborate with ML teams to accelerate their research and development, and enable them to develop the next generation of models and data curation - Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts Required Qualifications: - At least 1-3 years of LLM training in a production environment - Passionate about system optimization - Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc - Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster - Experience with multi-node LLM training and inference - Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc - Strong written and verbal communication skills to operate in a cross functional team environment - PhD or Masters in Computer Science or a related field Required Skills: LLM training, post-training methods, multi-node training, software engineering Important Skills: GPU cluster architecture, CUDA, Pytorch, transformers Nice-to-Have Skills: system optimization, PhD, Masters Benefits: Comprehensive health, dental and vision coverage, Retirement benefits, A learning and development stipend, Generous PTO, Commuter stipend