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Associate Recruiter (San Francisco based)

micro1· Talent / Recruiting
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Remote$40/hr - $65/hrfull-timePosted 1w ago

About the role

Associate Recruiter based in San Francisco (remote) focused on sourcing and securing top talent for data/AI roles in a fast-paced startup environment. Primarily remote with regular in-person presence at SF career fairs and events.

Responsibilities

  • Source and engage top-tier candidates through headhunting, networking, and digital platforms.
  • Manage end-to-end recruitment pipeline from outreach to onboarding.
  • Advise hiring managers on talent strategy and provide insights.
  • Maintain accurate applicant tracking records and report recruitment metrics.
  • Self-manage priorities and deliverables with high autonomy while working remotely.
  • Represent the customer’s team at SF-based career fairs and industry events bi-weekly.
  • Continuously refine sourcing strategies to adapt to startup needs.

Qualifications

  • 2-3 years of proven headhunting and recruitment experience, preferably in startup or tech-focused organizations.
  • Expertise in candidate sourcing, recruitment pipeline management, and talent acquisition best practices.
  • Exceptional organizational skills with ability to self-manage and deliver results remotely.
  • Strong stakeholder communication, collaboration, and relationship-building abilities.
  • Deep familiarity with the San Francisco talent market and local recruiting channels.
  • Adaptability and resilience to thrive amidst shifting priorities and fast-paced demands.
  • Demonstrated commitment to attending and actively participating in in-person SF career events.

Skills

Required:Head hunting / candidate sourcingRecruitment pipeline managementStakeholder communicationRemote work self-managementLocal SF market knowledge
Last updated Oct 25, 2026. Interested? Apply on the company site.

About micro1

Data lab to train frontier models & evaluate agents

We’re building the infrastructure for advancing intelligence through expert human data, real-world training environments, and contextual evaluations.

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