MTS - Research (Kernels & Hardware RL)

About Collinear At Collinear, we help teams fearlessly ship AI. About the Role We are looking for an MTS - Research (Kernels & Hardware RL) team member to help us build the data engine for frontier AI. You will develop high-fidelity reinforcement learning environments and evaluation stacks that teach advanced agents to write efficient GPU kernels and solve hardware optimization problems.

You will own environments end to end, from selecting meaningful tasks and reference implementations to building reliable scoring and preventing reward hacking.

Build Agentic Environments: Design diverse, executable tasks for GPU and accelerator kernels, low-level systems programming, and hardware-aware optimization. Extend into FPGA, RTL, or simulation workflows where your expertise can create meaningful challenges. Programmatic and Agentic Verification: Build reproducible correctness tests and performance graders, benchmark against trusted implementations, and harden execution sandboxes against timing exploits, test leakage, and reward hacking.

Close the Loop: Analyze agent trajectories and failure modes, curate high-signal tasks and data, and collaborate on post-training experiments that improve real capability across unseen workloads and hardware constraints. Collaborate: Work daily with the founders and research staff to shape the roadmap and push the state-of-the-art in AI reliability. Scale the Infrastructure: Build reliable compilation, execution, profiling, and evalu