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Mirendil

Member of Technical Staff, Post-Training, RL Infra

  • Seen live on Mirendil's site 2 days ago
  • Senior
Pay
$300k to $400k a year USD
Location
San Francisco
Open for
12+ days
First seen
Oct 23, 2026
Apply on Mirendil's site (opens in a new tab)

Posting record

No flags

Open 12+ days

The posting's record, oldest first
  1. Mirendil's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Mirendil, so its true age is longer.

Last checked Nov 2, 2026.

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What the posting discloses

Pay
$300k to $400k a year USD
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. (quoted from the posting)

Not stated: Real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

About the role

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.

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