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AI Tool-Use Evaluation Harness Engineer

Sofia Garcia

Full-time · Job · New_York

About the role

PyTorch, LangChain, and evaluation harnesses built to catch subtle model regressions are the core of what we build. If you'd rather build the tooling that proves a model actually works than ship another demo, this role is for you. You'll build an evaluation harness specifically for tool-use and function-calling behavior: does the model choose the right tool, pass correctly formatted arguments, and recover gracefully when a tool call fails. This is trickier to evaluate than plain text generation, and getting it wrong means shipping regressions straight to production agents. You'll define the evaluation methodology from scratch, working with our research team to make sure the harness catches the failure modes that actually matter in deployed agent systems.

Responsibilities

  • Design evaluation suites for tool-use and function-calling correctness
  • Build automated harness infrastructure that runs against every model candidate
  • Partner with research to define what 'correct' tool-use behavior means
  • Own the regression dashboard used before any model promotion decision

Requirements

  • 6+ years in ML engineering, with direct LLM evaluation experience
  • Strong PyTorch background and comfort building evaluation infrastructure
  • Experience with LangChain or comparable agent/tool-use frameworks
  • Track record catching subtle model regressions before production

Benefits

  • Fully remote position
  • Competitive salary plus equity
  • Health and dental insurance
  • Conference and research publication support

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Categories

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python langchain openai api pytorch

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Job Type

Full-time

Level

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Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python langchain openai api pytorch

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