RLEE - Low-Level Engineering & Kernel Inference Optimization

RLEE - Low-Level Engineering & Kernel Inference Optimization

RL Environments Kernel Optimization GPU/CUDA Compilers (LLVM/MLIR) PyTorch Extensions Distributed Inference (vLLM/NCCL)

Brief Description of the Role

We're hiring Low-Level Engineers to design and build RL environments that teach LLMs kernel development, hardware optimization, and systems programming. The goal is to create realistic feedback loops where models learn to write high-performance code across GPU and CPU architectures.

This is a remote contractor role with ≥4 hours overlap to PST and advanced English (C1/C2) required.

About the Company

Preference Model is building the next generation of training data to power the future of AI. Today's models are powerful but fail to reach their potential across diverse use cases because so many of the tasks that we want to use these models are out of distribution. Preference Model creates RL environments where ...