--- title: 'Member of Technical Staff, Post-Training, RL Environments at Mirendil' canonical: 'https://feeny.ai/job/member-of-technical-staff-post-training-rl-environments-mirendil-san-francisco-4xhaghhhy75v' type: 'job' last_seen: '2026-09-11' --- # Member of Technical Staff, Post-Training, RL Environments at Mirendil - **Company:** Mirendil - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-06-24 - **Last confirmed live:** 2026-09-11 - **Apply:** https://jobs.ashbyhq.com/mirendil/9fd66ea3-817c-481a-b5c5-357dc993e18c ## 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 a research engineer to build the data systems and execution environments that power reinforcement learning at Mirendil. The quality of our models depends directly on the quality of the data and environments we train on; you will own those systems end-to-end. Some example areas you might work on (not limited to): - Build and automate data collection pipelines for complex, long-horizon RL tasks. - Build robust systems to identify and prevent reward hacking. - Build scalable sandboxed execution environments for realistic tasks involving potentially multiple agents, nodes, and users. - Design systems to estimate the influence of training environments on production model behavior. - Collaborate with teams across the stack to identify potential axes of improvements in production model behavior, and develop training environments to push these axes. If you're excited about building the data and environment infrastructure that determine what our models learn, 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. ## About Mirendil ## Company Overview - **One-liner**: Mirendil is building an AI system that automates AI research and development, with the goal of creating a self-improving loop that accelerates scientific discovery. - **Entity Type**: Private (Seed stage; raised $200M) - **Headquarters**: San Francisco, California, USA - **Founded**: Early 2026 - **Founders**: Behnam Neyshabur and Harsh Mehta ## Core Business - **Primary industry**: Artificial Intelligence / AI Research & Development - **Target customers**: B2B – initially AI researchers and engineers, but eventually scientists and domain experts (e.g., biology labs, drug discovery teams) who need frontier AI capabilities without building a full AI lab. - **Mission**: “Democratizing frontier AI R&D to accelerate science and technology.” The company believes self-accelerating AI R&D is the most direct path to solving humanity’s pressing problems. ## Products & Services - **Mirendil Platform**: A proprietary AI R&D system that trains frontier models specialized in AI research tasks (e.g., experimental design, hyperparameter search, model evaluation, code writing, debugging). The platform is designed to autonomously loop over research and engineering problems, controlling its own GPUs and improving over time with minimal human input. **Status**: Not yet shipped; under development. ## Market Standing - **Valuation**: $1 billion (as of June 2026 seed round) - **Key Metric (Funding)**: $200 million raised in seed round – one of the largest AI seed rounds ever. - **Notable Investors/Partners**: Andreessen Horowitz (co-lead), Kleiner Perkins (co-lead), NVIDIA (participant). - **Growth Signals**: - Raised $200M at $1B valuation just months after founding. - Founding team of 20+ researchers and engineers recruited from Anthropic, xAI, Google DeepMind, and OpenAI. - Founders Behnam Neyshabur (co-inventor of SAM optimizer, ex-Google, ex-Anthropic) and Harsh Mehta (ex-Google, ex-Anthropic, initiated automated AI R&D efforts) have deep frontier AI experience. - Targeted at compressing research cycles from months to days. ## Competitive Advantages - **Self-Accelerating Loop**: The product is not just a model but a system that improves itself – “the loop is the product.” This creates a compounding advantage if it works. - **Singular Focus**: The entire company is rebuilt from scratch around AI doing AI research, unlike traditional labs that use AI as a tool. - **Top-tier Talent Density**: With only ~20 people, the team includes some of the most accomplished young researchers from the leading AI labs. - **Strategic Investors**: Backing from a16z, Kleiner Perkins, and NVIDIA provides credibility, capital, and potential infrastructure access. ## Strategic Focus - **Immediate goal**: Build the system that can autonomously perform AI R&D, making frontier research accessible to non-AI experts. - **Long-term vision**: Democratize frontier AI R&D so that any lab (drug discovery, chemistry, biology, robotics) can leverage it without becoming a frontier AI lab themselves. - **Current priorities**: Train models exceptional at AI research; build infrastructure for automated experimentation, evaluation, and iteration; keep the team small and high-compound. ## Why Work Here - **Engineering culture**: “Small team, singular focus. We hire to compound, not to grow.” The team of ~20 operates with high autonomy and ownership. - **Cutting-edge work**: Opportunity to work on one of the most ambitious AI projects – automating the very process of AI research. - **Team composition**: Colleagues from Anthropic, xAI, DeepMind, OpenAI; founders known for foundational contributions (SAM optimizer, Blueshift/Mirerva). - **Work environment**: Based in San Francisco; likely in-office given the intensity of the work (remote/hybrid policy not publicly detailed). - **Notable perks**: Direct exposure to frontier model training and infrastructure; chance to shape a company from its earliest stage. ## Sources 1. [mirendil.com](https://mirendil.com/) 2. [mirendil.com/careers.html](https://mirendil.com/careers.html) 3. [kleinerperkins.com](https://www.kleinerperkins.com/perspectives/mirendil-building-the-system-that-builds-systems/) 4. [a16z.news](https://www.a16z.news/p/investing-in-mirendil) 5. [techfundingnews.com](https://techfundingnews.com/ex-anthropic-researchers-raise-200m-just-weeks-after-quitting-to-build-ai-that-creates-better-ai/) ## Other roles at Mirendil - [Executive Assistant & Operations](https://feeny.ai/job/executive-assistant-operations-mirendil-san-francisco-c06e01p1zc49) — San Francisco, CA - [Member of Technical Staff, Designer](https://feeny.ai/job/member-of-technical-staff-designer-mirendil-san-francisco-kzprmabdengf) — San Francisco, CA - [Member of Technical Staff — Company Building](https://feeny.ai/job/member-of-technical-staff-company-building-mirendil-san-francisco-pgxgc7w41ejt) — San Francisco, CA - [Member of Technical Staff, Inference](https://feeny.ai/job/member-of-technical-staff-inference-mirendil-san-francisco-sgh26y1tszjq) — San Francisco, CA - [Member of Technical Staff, Model Evaluation](https://feeny.ai/job/member-of-technical-staff-model-evaluation-mirendil-san-francisco-xznefyyvx6s7) — San Francisco, CA - [Member of Technical Staff, Post-Training, RL Infra](https://feeny.ai/job/member-of-technical-staff-post-training-rl-infra-mirendil-san-francisco-szsxpdqdgqj8) — San Francisco, CA - [Member of Technical Staff, Post-Training, RL](https://feeny.ai/job/member-of-technical-staff-post-training-rl-mirendil-san-francisco-ep9mzj7wn4a1) — San Francisco, CA - [Member of Technical Staff, Kernels](https://feeny.ai/job/member-of-technical-staff-kernels-mirendil-san-francisco-yjht6zkjbnqh) — San Francisco, CA - [Member of Technical Staff, Pretraining](https://feeny.ai/job/member-of-technical-staff-pretraining-mirendil-san-francisco-7f3vnjtsrh49) — San Francisco, CA - [Member of Technical Staff, Infrastructure](https://feeny.ai/job/member-of-technical-staff-infrastructure-mirendil-san-francisco-crx8w13g6s47) — San Francisco, CA