Preference Model seeks experienced Machine Learning Engineers for its Low Level/Kernels Capabilities team. Join to design and build advanced RL environments in a collaborative setting.In this role, you will blend research and engineering to develop cutting-edge reinforcement learning environments from scratch. Your tasks will include choosing domains, designing projects, building infrastructure, and ensuring robustness against manipulation. By working on the lowest layers of the ML stack, you'll tackle challenges where frontier models traditionally struggle.Key Responsibilities:Design low-level focused RL environments for targeted modelsDevelop deterministic scoring systems to prevent gamingChoose key environments for RL developmentBuild and maintain kernel scoring and task designEnsure robust performance and correctness under diverse scenariosRequirements:Strong C/C++/CUDA skills with low-level experienceProficient engineering-quality Python codingFamiliarity with hardware-aware programmingExtensive kernel development experienceCapable of owning projects with minimal supervisionLeverage your expertise in kernel development to advance the potential of RL at Preference Model.#J-18808-Ljbffr

📌 Machine Learning Engineer At Preference Model (Toronto)
🏢 Preference Model
📍 Toronto