Member of Technical Staff, Post-Training, RL Infra
Most applications go out cold — see where you stand first. No sign-up to start.
Don't just apply. Show up ready.
Olive works from this exact posting — no sign-up to start.
At a glance
Job overview
Mirendil is seeking engineers to build the post‑training stack for frontier reinforcement‑learning models, bridging research and infrastructure. The role focuses on designing reliable large‑scale RL training infrastructure, implementing performance optimizations, creating evaluation and benchmarking tools, and developing data collection pipelines that integrate human feedback into training. Candidates will collaborate across teams to accelerate RL research at scale.
Skills & qualifications
Skills
Full job description
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.
You've read the whole posting — now see how you match it.