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Positive and Unlabelled Learning: Recovering Labels for Data Using Machine Learning
Problem It's often the case that companies want to implement machine learning for a given task-let's say, to perform classification on data-but are cursed with the problem of having insufficient or unreliable labels for that data. In these cases, companie
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Report
Tech stack
Technologies named in job postings at Label Your Data over the last 12 months, by layer, with the share of postings for each.
Technologies in use
4
Postings analysed
8
Stack modernity
58/100
Cloud & platforms
Roboflow
Figma
Practices & domains
Digital Twin
Machine Learning
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Growth
Hiring Momentum
75/100
Scaling fast
Open positions
2
1 opened / 0 closed in 30 days
Median time-to-fill
15 days
faster than 66% of the market
ATS activity
Every ~6 hours
Today
Hiring Dynamics
0%
Hiring Focus
The percentage next to each role is its share of the company's job openings over the last 90 days; the arrow shows the shift versus the previous period.
AI/ML
64% ▼
Operations
18% ▼
Legal
9% ▲
Marketing
9% ▼
Activity Timeline
New location: Ivano-Frankivsk
Oct 2026
New location: Lutsk
Oct 2026
Added GDPR to stack
Oct 2026
New location: Uzhhorod
Oct 2026
New location: Chernivtsi
Oct 2026
New location: Lviv
Oct 2026
New location: Odesa
Oct 2026
Removed Windows from stack
Sep 2026
Added Machine Learning to stack
Sep 2026
Added Windows to stack
Sep 2026
Added Figma to stack
Sep 2026
+5 jobs in a week
Sep 2026
Offices
Where the company hires and what each office is for
Cities
1
Hiring now
1
Countries
1
Busiest office
Kyiv
Kyiv
Ukraine
HQ
2 open roles 2 posted in 90 days 100% remote
hires for Legal, Marketing
