Member of Technical Staff, Post-Training, RL Infra
Summary
Engineer on the post-training team of a frontier AI research company, building and scaling the RL training infrastructure for reasoning models — reliability, performance optimization, evaluation/benchmarking tooling, and data/feedback pipelines that connect human signal and reward modeling to production training runs.
Mirendil
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.
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
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 possible at scale, we'd love to hear from you.
We offer a base salary of $300,000–$400,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.