Mirendil — a frontier lab building systems that excel at AI R&D. Backed by Kleiner Perkins.
About the role
We are looking for engineers to help build the post-training stack for frontier reasoning models. This role sits at the intersection of research and infrastructure. You will work to push the scale of our RL stack, whether it is novel recipe ideas, reliability, or performance. Some example areas you might work on (not limited to): Design and build reliable infrastructure for large-scale RL training
More about this role
Mirendil is a tech-first company focused on solving core bottlenecks that unlock step-change acceleration across science and technology. Our first goal is to democratize frontier AI R&D across scientific disciplines. We are building a frontier AI research company and training our own models end-to-end.
We are looking for engineers to help build the post-training stack for frontier reasoning models. This role sits at the intersection of research and infrastructure. You will work to push the scale of our RL stack, whether it is novel recipe ideas, reliability, or performance. Some example areas you might work on (not limited to):
Design and build reliable infrastructure for large-scale RL training
Implement novel performance optimizations across the training stack
Develop evaluation and benchmarking infrastructure to measure model progress, throughput, and uptime
Build data collection and feedback pipelines that close the loop between human signal, reward modeling, and training
Collaborate with multiple teams to rapidly iterate on RL algorithms and get experiments into production training runs
If you're excited about building the infrastructure that makes frontier RL research...
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