Mirendil

Member of Technical Staff, Post-Training, RL

San Francisco · Staff+

Sponsorship not specified$300k-$500kDetected 28 days ago

Research

About the role

This role sits at the point where model capability, training dynamics, data, verification, and infrastructure all meet.
The best work here will involve both: forming hypotheses about training behavior, implementing them in real systems, running large-scale experiments, reading the resulting traces carefully, and turning the lessons into the next training run.

Develop and iterate on RL, SFT, and distillation recipes.
Develop methods for assigning useful feedback across long trajectories, where sparse rewards, credit assignment, exploration, and verification all become harder.
Build intuition and tooling for when off-policy data helps, when it hurts, and how to control the resulting instabilities.
Build robust verification pipelines for tasks where correctness can be checked automatically or semi-automatically.
Study the tradeoffs between specialization and generality, and design training mixtures that improve all capabilities together.
Develop a deep empirical understanding of training runs.
Diagnose regressions, separate real improvements from noise, design better ablations, and build the probes and analyses needed to make post-training less opaque.
Verification and reward quality: Build robust verification pipelines for tasks where correctness can be checked automatically or semi-automatically.
If you're excited about building the infrastructure that makes frontier RL research possible at scale, we'd love to hear from you.

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.
Our work spans areas such as model training, reinforcement learning, reasoning systems, and infrastructure for large-scale experiments.
Researchers are also expected to have strong engineering skills.

We offer a base salary of $300,000–$500,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.

We offer a base salary of $300,000-$500,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.

We are looking for research engineers to help build the post-training stack for frontier reasoning models.

This listing is sourced directly from Mirendil's careers page and normalized into a canonical job model.