---
title: 'Member of the Technical Staff at Poetiq'
canonical: 'https://feeny.ai/job/member-of-the-technical-staff-poetiq-los-altos-8rw11ea4hwre'
type: 'job'
last_seen: '2026-11-06'
---

# Member of the Technical Staff at Poetiq

- **Company:** Poetiq
- **Location:** Los Altos, CA
- **Compensation:** $150k–$500k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-25
- **Last confirmed live:** 2026-11-06
- **Apply:** https://jobs.ashbyhq.com/poetiq/5133494e-d8cc-4663-b340-d6f0e6e77a49

## Job description

Recursive Self Improvement is the most important frontier in AI research. We’re hiring a team of the best researchers and engineers dedicated to advancing RSI. If you’re driven to advance the frontiers of AI through RSI and optimization, come apply to be a Member of the Technical Staff at Poetiq. This is a single, flexible technical role that spans both the algorithmic core of our RSI loop and the high-performance systems that let it run autonomously at scale. Every MTS shares ownership of the same mission: advance the frontier of AI through RSI.

## What You'll Do

Your day-to-day depends on your focus, but the shared surface area includes:

- Improve the RSI loop — design and build the core algorithms that drive system-level self-improvement.
- Push reasoning strategy — propose and test novel, task-specific reasoning strategies; probe LLMs to surface latent knowledge; build data-efficient methods for finding optimal strategies per task.
- Build dynamic harnesses — synthesize task-specific execution environments on the fly, even as the system concurrently rewrites its own codebase.
- Architect orchestration — design clean abstractions for highly parallelized workflows, turning fragmented signal from thousands of parallel, asynchronous LLM interactions into coherent, high-performance reasoning chains.
- Probe capability boundaries — build diagnostic pipelines that separate genuine knowledge gaps from tooling limits (e.g., live retrieval) and reasoning/composition failures.
- Close the feedback loop — route knowledge-gap failures into SFT data pipelines; turn reasoning/composition failures into verifiable, exact-match RL tasks.
- Run infrastructure at scale — build and maintain high-performance infrastructure against external, third-party LLMs (experimental, large-scale, and publicly deployed) so research and optimization loops run reliably without human intervention.
- Keep it interpretable — every loop stays transparent code, explicit prompts, and clear diagnostics, never opaque parameter updates.

## What You'll Need

Everyone on technical staff:

- Autonomy to turn both well-defined and highly ambiguous ideas into production-grade reality.
- First-principles understanding of LLM reasoning and failure modes, plus hands-on experience with LLM “quirks.”
- You want to build loops where the system learns from each problem it solves and gets better at the next one.
- Fully on-site in Los Altos — this is a high-bandwidth, whiteboard-heavy, low-ego, in-person team, and that's a fit requirement, not a preference.
- Commitment to code quality, rigorous testing, performance profiling, deliberate architectural design, and clear communication.

## Our Team & Engineering Culture

We are a high-leverage team of 10 engineers and researchers. We thrive in an in-office environment built around high-bandwidth collaboration, rapid whiteboarding, and low-ego problem solving. Our engineering culture is highly collaborative, mentorship-driven, and deeply inclusive. We value clear communication, rigorous testing, and deliberate architectural design. At Poetiq, you won't just be optimizing weights on the periphery; you will be core to designing the interpretable reasoning architectures of the future.

## About Poetiq

## Company Overview
- **One-liner**: Poetiq builds a self-improving reasoning system that sits on top of any frontier large language model, enabling automated recursive self-improvement for complex problem-solving.
- **Entity Type**: Private (Seed stage – $45.8M raised)
- **Headquarters**: Mountain View, California, United States
- **Founded**: 2025
- **Founders**: Not publicly disclosed (founding team includes veterans from Google and DeepMind)

## Core Business
- **Primary industry/industries**: Artificial Intelligence, AI Infrastructure, Machine Learning
- **Target customers**: B2B – enterprises and organizations that need reliable, high-performance reasoning for complex workflows (e.g., code generation, scientific research, data synthesis)
- **Mission or purpose statement**: “The fastest path to safe superintelligence. Paved with better reasoning.” [poetiq.ai](https://poetiq.ai/)

## Products & Services
- **[Meta-System]**: A proprietary reasoning engine that wraps around any LLM (ChatGPT, Claude, Gemini, etc.) to probe, extract, and synthesize fragmented knowledge. It uses recursive self-improvement loops to learn task-specific reasoning strategies with very little data (hundreds of data points instead of millions), enabling dramatic performance gains without retraining the underlying model. It has achieved state-of-the-art results on benchmarks such as ARC-AGI, LiveCodeBench, and Humanity’s Last Exam. [poetiq.ai](https://poetiq.ai/)

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total Funding – $45.8M in a single Seed round (closed in late 2025 / early 2026)
- **Notable Investors/Partners**: Surface Ventures, FYRFLY Venture Partners, Y Combinator, 468 Capital, Operator Collective, NeuronVC, and HICO. [poetiq.ai/posts/seed_funding/](https://poetiq.ai/posts/seed_funding/)
- **Growth Signals**: 
  - Shattered the ARC-AGI-2 state-of-the-art with 54% accuracy (first to break 50%) at a cost of $30.57 per problem. [linkedin.com/company/poetiq](https://www.linkedin.com/company/poetiq)
  - Achieved SOTA on Humanity’s Last Exam and SimpleQA.
  - 7 employees with a monthly headcount growth of +22.2%; LinkedIn followers grew 4.2% monthly to ~2,400. [builtin.com/company/poetiq](https://builtin.com/company/poetiq)
  - Proven that the system can lift performance of smaller, cost-efficient models to compete with frontier reasoning models (e.g., matching Gemini Deep with a Flash model). [linkedin.com/company/poetiq](https://www.linkedin.com/company/poetiq)

## Competitive Advantages
- **Data‑efficient self‑improvement**: Poetiq’s method requires only hundreds of data points rather than the millions needed for reinforcement‑learning‑based post‑training, making it practical for most real‑world domains.
- **Model‑agnostic architecture**: The system sits on top of any LLM and adapts to each model’s quirks, meaning customers are not locked into a single model provider.
- **Continually improving**: Each solved problem automatically improves the system’s reasoning strategies, creating a compounding flywheel effect.
- **Team expertise**: The founding team has 72 years of combined experience at Google and DeepMind, giving them deep first‑principles understanding of LLMs and their failure modes. [poetiq.ai](https://poetiq.ai/)

## Strategic Focus
- **Scale the team and infrastructure**: With the fresh seed funding, Poetiq is aggressively hiring AI Scientists and AI Engineers to accelerate research and build a robust platform for commercial deployment. [poetiq.ai/careers/](https://poetiq.ai/careers/)
- **Commercialization**: Moving from research breakthroughs to practical, reliable reasoning systems that solve business workflows. “With this capital, we are accelerating the development of our core technology—a system that automatically creates expert agents capable of dramatically outperforming their underlying language models.” [poetiq.ai/posts/seed_funding/](https://poetiq.ai/posts/seed_funding/)
- **Open‑access vision**: “In a few months, we will be offering it for free” – suggesting a freemium or democratized access model to drive adoption. [poetiq.ai](https://poetiq.ai/)

## Why Work Here
- **Culture**: A small, fast‑moving team of top‑tier researchers and engineers (currently ~7 people) with a high‑trust, high‑autonomy environment. The careers page emphasizes “insanely passionate scientists and engineers” and “crazy ideas.” [poetiq.ai/careers/](https://poetiq.ai/careers/)
- **Work policy**: On‑site in Mountain View, California. [builtin.com/company/poetiq](https://builtin.com/company/poetiq)
- **Engineering culture**: Python‑heavy; focus on building complex agentic systems, multi‑step execution frameworks, and high‑performance infrastructure that interacts with external LLMs. Engineers are expected to work autonomously and turn ambiguous ideas into reality.
- **Impact**: Opportunity to contribute directly to the core algorithms and infrastructure of what the company calls “the fastest path to superintelligence.” The team is small enough that every hire has outsized influence on the product and research direction.

## Sources
1. [poetiq.ai](https://poetiq.ai/)
2. [poetiq.ai/careers/](https://poetiq.ai/careers/)
3. [builtin.com/company/poetiq](https://builtin.com/company/poetiq)
4. [linkedin.com/company/poetiq](https://www.linkedin.com/company/poetiq)
5. [poetiq.ai/posts/seed_funding/](https://poetiq.ai/posts/seed_funding/)

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