
Building a Global TA Engine: Lessons from Remote’s Hyper-Growth with Anastasia Pshegodskaya
In this episode, we sit down with Anastasia Pshegodskaya, Director of TA at Remote, to unpack how the company scaled from 200 to nearly 2,000 people in just four years.
We explore the realities of hiring without borders, managing intense applicant volume, building culture asynchronously, navigating compensation across countries, and experimenting with AI-powered first-round interviews.
Whether you lead Talent Acquisition, People, HR operations, or you're scaling a global team, this conversation is packed with insights about building a TA function for the next decade of work.
Timestamps
01:15 Hiring globally: what changes when the world becomes your talent pool
03:02 Scaling Remote: from 200 to 2,000 employees
04:48 Building TA foundations while the company hyper-scales
06:32 Why quality over quantity became the turning point
08:41 How Remote structures recruiters across time zones
10:52 The communication challenge of fully remote teams
12:30 AI-powered TA Digest bot and async communication
14:03 30,000 applications a month: how Remote filters intelligently
16:12 AI interviews as step one: what worked and what didn’t
18:10 Creating belonging through social channels and onboarding
20:36 Compensation strategy: geo-tiers, fairness, relocation
24:55 Misconceptions about remote work and high performance
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Connect with us on LinkedIn: https://www.linkedin.com/company/matchr/
Get in touch with us: https://www.matchr.io/who-we-are/contact/
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Connect with Anastasia Pshegodskaya: https://www.linkedin.com/in/pshegodskaya/
Connect with Adriaan Kolff: https://www.linkedin.com/in/adriaankolff/
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RSS feed: https://media.rss.com/leaders-in-talent/feed.xml
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Need a Recruitment Support? Embed Matchr’s expert recruiters directly into your team. Seamless integration for immediate impact on your hiring process.
Learn more: https://matchr.io
Information
- Show
- FrequencyUpdated Biweekly
- PublishedDecember 8, 2025 at 8:00 AM UTC
- Length35 min
- Episode20
- RatingClean