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 models
- Develop deterministic scoring systems to prevent gaming
- Choose key environments for RL development
- Build and maintain kernel scoring and task design
- Ensure robust performance and correctness under wide-ranging scenarios

Requirements:

- Strong C/C++/CUDA skills with low-level experience
- Proficient engineering-quality Python coding
- Familiarity with hardware-aware programming
- Extensive kernel development experience
- Capable of owning projects with minimal supervision

Leverage your expertise in kernel development to advance the potential of RL at Preference Model.

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