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Microsoft

Talent Sourcer, AI

Career Insights for Recruiter (General)

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What they do

A Recruiter works for a company or organization to recruit qualified candidates for open positions, or works with a recruiting agency to identify candidates and match jobseekers with job placements. May specialize in recruiting professionals in a particular industry, or specialize in recruiting at colleges.

$72,812 / year median in Washington

-20% projected decline

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Job Description

Stakeholder Collaboration Present market insights, search progress, and candidate recommendations with clarity and confidence, particularly in ambiguous or evolving searches.
Drive rigor in calibration:
challenge assumptions, align early, and advocate for sourcing approaches that optimize for long-term outcomes. Guide hiring teams toward inclusive and differentiated sourcing strategies. Build long-range pipelines around critical profiles using technical taxonomies, publication review, and trend-based forecasting. Design and execute research-forward sourcing strategies to surface rare, highly specialized AI/ML talent. Contribute to sourcing missions that span 6-8 weeks with clear goals: mapped markets, validated pipelines, and calibrated submissions. Navigate multiple, concurrent searches across evolving profiles with urgency and precision. Contribute to team learning and global connectivity through knowledge sharing and collaboration. Bachelor's Degree AND 4+ years talent acquisition experience (e.g., recruiting, sourcing), HR experience, or industry experience related to role Bachelor's Degree AND 8+ years talent acquisition experience (e.g., recruiting, sourcing), HR experience, or industry experience related to role OR Master's Degree AND 6+ years talent acquisition experience (e.g., recruiting, sourcing), HR experience, or industry experience related to role OR equivalent experience. 4+ years of experience analyzing talent market trends to consult hiring managers on recruiting strategies 2+ years of experience sourcing Artificial Intelligence (AI) talent Experience sourcing for frontier AI labs, early-stage startups, or technical teams building large-scale ML systems Deep familiarity with open-source and research ecosystems: GitHub, Arxiv, Hugging Face, Stack Overflow, and academic conferences (e.g., Neur
IPS, ICML, CVPR
) Proven success using Boolean/X-ray logic, publication-based sourcing, and outreach beyond traditional channels Comfort working in fast-paced, dynamic environments where velocity, experimentation, and ownership are key