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Poetiq

Develops AGI via recursive self-improvement

Member of the Technical Staff

AI ResearchConfirmed live in the last 24 hours
Full-timeLos Altos, CA, USA$150k - $500k /yr

About the Job

Requirements

  • Autonomy to turn well-defined and highly ambiguous ideas into production-grade reality.
  • First-principles understanding of large language model reasoning and failure modes, plus hands-on experience with large language model quirks.
  • Fully on-site in Los Altos; in-person attendance is required.
  • Commitment to code quality, rigorous testing, performance profiling, deliberate architectural design, and clear communication.

Responsibilities

  • Design and build core algorithms that drive system-level self-improvement in the recursive self-improvement loop.
  • Propose and test novel, task-specific reasoning strategies; probe large language models to surface latent knowledge; and build data-efficient methods for finding optimal strategies per task.
  • Synthesize task-specific execution environments dynamically, including while the system concurrently rewrites its own codebase.
  • Design clean abstractions for highly parallelized workflows, turning signals from thousands of parallel, asynchronous large language model interactions into coherent, high-performance reasoning chains.
  • Build diagnostic pipelines that distinguish genuine knowledge gaps from tooling limits, such as live retrieval, and from reasoning or composition failures.
  • Route knowledge-gap failures into supervised fine-tuning data pipelines and turn reasoning or composition failures into verifiable, exact-match reinforcement-learning tasks.
  • Build and maintain high-performance infrastructure against external third-party large language models so research and optimization loops run reliably without human intervention.
  • Keep every loop transparent through code, explicit prompts, and clear diagnostics rather than opaque parameter updates.

About the Company

Poetiq

Develops AGI via recursive self-improvement

Poetiq focuses on developing Artificial General Intelligence (AGI) by enabling safe, recursive self-improvement rather than training ever-larger data models. Its sole product is AGI itself, pursued through a strategy that uses the knowledge already embedded in existing AI models to achieve faster, more efficient progress toward AGI. Compared with competitors, Poetiq does not primarily scale data; it leverages the strengths of current models and recursive self-improvement, guided by experienced AI researchers from Google/DeepMind who aim to build a safer, scalable path to AGI. The company’s goal is to reach and advance AGI and go beyond, continually improving its system while focusing on safety and efficiency.

Company size
11-50
Company stage
Seed
Total funding
$45.8M
Headquarters
Mountain View, CA
Founded
2025

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