# Member of the Technical Staff at Poetiq

Member of the Technical Staff at Poetiq in Los Altos. On-site, full-time, paying $150k–$500k. Posted September 25, 2026.

- Company: Poetiq
- Location: Los Altos
- Workplace: On-site
- Job type: Full-time
- Pay: $150k–$500k
- Posted: 2026-09-25
- Apply: https://jobs.ashbyhq.com/poetiq/5133494e-d8cc-4663-b340-d6f0e6e77a49/application
- Source: https://jobmagic.ai/jobs/member-of-the-technical-staff-poetiq-bh29xk

## 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.