The Scale of What Happened
The numbers are jarring when you put them together. From January 2022 through the end of 2025, roughly 680,000 tech workers were laid off at companies tracked by Layoffs.fyi, with the bulk concentrated in 2022 and 2023. But 2024 and 2025 brought a second, quieter wave that affected a different profile of worker and got less coverage because the companies involved were less famous.
Tech Layoffs by Year (U.S., tracked companies)
2023 was the peak by raw numbers. But the 2024-2025 wave hit differently. The 2022-2023 cuts were largely about companies that had over-hired during the pandemic correction. Many of the affected workers were mid-level engineers and product managers who found new jobs within 2-4 months. The 2024-2025 cuts were more surgical. Companies like Google, Microsoft, and Amazon made specific team eliminations, often targeting roles that overlapped with AI automation capability.
Which Roles Were Cut Most
41%
of 2024-2025 tech layoffs affected non-engineering roles: recruiters, HR, marketing, and ops (Layoffs.fyi analysis, 2025)
The composition of the 2024-2025 cuts is telling. In 2022-2023, engineers bore the largest share. By 2024, recruiting teams were decimated first. Many companies that had built out large talent acquisition functions during the hiring boom had nowhere to put those people once hiring volumes dropped 60-70%.
The role categories most affected in 2024-2025:
- Technical recruiters: Estimated 35,000 positions eliminated across the industry, many at companies that had hired aggressively in 2021-2022
- Program and project managers: Many tech companies discovered that flatter structures with AI-assisted tracking tools could absorb coordination work
- Content and communications roles: Particularly at mid-tier tech companies where AI writing tools made generalist content roles harder to justify
- QA engineers: AI-assisted testing tools reduced the headcount needed for manual QA by a meaningful amount at larger companies
- Middle management: Several large tech companies publicly announced manager-to-IC ratio reductions as a deliberate strategy
How Long Job Searches Actually Took
The 2024-2025 job search data is sobering for laid-off tech workers accustomed to 2021-era hiring timelines. In 2021, a mid-level software engineer could reasonably expect 3-5 offers within 6 weeks of starting a search. By 2024, the same profile averaged 4-6 months to an offer.
| Role | Avg. Search Time (2021) | Avg. Search Time (2024-25) |
|---|---|---|
| Senior Software Engineer | 5 weeks | 18 weeks |
| Product Manager | 7 weeks | 22 weeks |
| Technical Recruiter | 3 weeks | 28 weeks |
| Data Scientist | 6 weeks | 16 weeks |
| UX Designer | 8 weeks | 24 weeks |
What Happened to Salaries
The salary story has two chapters. Total compensation at top-tier companies (FAANG and their peers) held steady or increased, because those companies reduced headcount while protecting the people they kept. If anything, the remaining engineers at Google and Meta in 2025 are better compensated than their 2022 counterparts because the companies eliminated lower-performing employees during cuts.
At mid-tier companies and startups, the story is different. Salary bands compressed as supply of candidates exceeded demand. Engineers who were earning $170K at a Series B startup in 2022 found they were competing for roles at $140K in 2024. The premium for "startup risk" compressed because the job market had flipped.
What This Means for Job Seekers Now
The market in early 2026 is not 2021, but it's also not 2023. Hiring has resumed at a meaningful pace, particularly in AI infrastructure, healthcare technology, and defense/national security tech. The companies doing the most hiring are often not the household names, and the roles they're hiring for require a slightly different skill profile than the 2021 wave.
A few practical takeaways. First, search timelines are still longer than pre-2022 norms. Plan for 3-5 months. Second, network-sourced opportunities are converting at much higher rates than cold applications. The application-to-interview ratio on major job boards deteriorated sharply as the number of applicants per role increased. Third, demonstrating AI tool fluency in your application and interview process is now a meaningful differentiator across virtually every role category.