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Bravebird

Founding Applied ML Engineer

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Description

You'll build the core intelligence behind our agents (reasoning, planning, tool use, memory, grounding, and evaluation) across chat, voice, and computer-use interfaces. This is a founding-level, high-ownership role: you'll work directly with the founders and customers, shape the technical direction, and ship systems that run in a high-stakes, regulated environment.


Responsibilities:

  • Design and build reasoning and planning systems for real production workflows.
  • Build tool orchestration, grounding, and execution frameworks that hold up against messy real-world systems.
  • Develop memory, context, and state management for long-running, multi-step tasks.
  • Build evaluation systems that measure correctness, reliability, and performance.
  • Make chat, voice, and UI-based agents work together dependably.
  • Turn research ideas into production systems.
  • Help define engineering culture, standards, and technical direction.


Requirements:

  • 5+ years of software engineering, with strong backend / distributed systems fundamentals.
  • 2+ years building and shipping LLM or agentic systems in production (real users, not POCs).
  • Hands-on experience with evals, retrieval, memory, and grounding for LLM systems.
  • Strong knowledge of Python
  • Comfort with ambiguity and a bias toward reliable, measurable, testable systems.
  • Product sense: you care about real users and real outcomes.
  • Clear communication and strong collaboration.

Skills

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See also

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