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Member of Technical Staff, Agents

πŸ”₯ 14 hours ago
PythonSQLDjangoReact
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πŸ“œ Description

  • Build agents that complete delegated work end to end for real users.
  • Define success measures for agent tasks and maintain representative evaluations.
  • Develop and validate agent capabilities before release to users.
  • Investigate production failures and fix underlying causes.
  • Build systems to detect known and emerging failure patterns at scale.
  • Improve agent recovery from tool or website failures and help engineers measure the impact of changes.

πŸ› οΈ Requirements

  • At least 3 years of data science or machine learning experience building evaluation systems, metrics, or quality measurement for products.
  • Production-quality Python and SQL skills, including experience analyzing large datasets and building automated pipelines.
  • Experience designing evaluation frameworks, datasets, measurable criteria, and appropriate metrics.
  • A track record delivering production AI, machine learning, agent, or agent-evaluation systems for real users.
  • Experience improving agent reliability, owning systems end to end, and measuring results in production.
  • Familiarity with statistics, experiment design, and realistic end-to-end simulations; experience with fine-tuning, post-training, or reinforcement learning is valuable.
  • Experience with Python, Django, React, and TypeScript; familiarity with evaluation tools such as Braintrust or Raindrop is useful.
  • Demonstrated progression and sustained experience in a role, with the ability to work through ambiguity and ship quickly.

✨ Benefits

  • Base salary is $200,000 to $300,000 USD annually. Visa sponsorship is not available.
Full job description

About the Role

Join a small, senior team building autonomous AI assistants for executive workflows. You will develop agent capabilities and evaluation systems that help ensure real-world tasks are completed reliably, with measurable quality.

What You'll Do

  • Build agents that complete delegated work end to end for real users.

  • Define reliable measures of success for agent tasks and maintain representative evaluations.

  • Develop new agent capabilities and validate them before they reach users.

  • Investigate production failures and deliver fixes that address underlying causes.

  • Build systems to detect known failure patterns and emerging issues at scale.

  • Improve agent recovery when tools or websites fail.

  • Create repeatable methods for engineers to measure the impact of agent changes.

What We're Looking For

  • At least 3 years of data science or machine learning experience building evaluation systems, metrics, or quality measurement for products.

  • Production-quality Python and SQL skills, including experience analyzing large datasets and building automated pipelines.

  • Experience designing evaluation frameworks, datasets, measurable criteria, and appropriate metrics.

  • A track record delivering production AI, machine learning, agent, or agent-evaluation systems for real users.

  • Experience improving agent reliability, owning systems end to end, and measuring results in production.

  • Familiarity with statistics, experiment design, and realistic end-to-end simulations; experience with fine-tuning, post-training, or reinforcement learning is valuable.

  • Experience with Python, Django, React, and TypeScript; familiarity with evaluation tools such as Braintrust or Raindrop is useful.

  • Demonstrated progression and sustained experience in a role, with the ability to work through ambiguity and ship quickly.

Compensation & Benefits

Base salary is $200,000 to $300,000 USD annually. Visa sponsorship is not available.

Location

On-site in Palo Alto, California, with four days a week in the office.

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