Member of the Technical Staff

We're hiring a Member of the Technical Staff to help build our self-improving reasoning engine end to end. 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. Depending on your background, you'll lean into deep algorithmic research, rigorous systems engineering, or a genuine hybrid of both. 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.

Employment type
FullTime

Work arrangement
No