Reports

A snapshot of pipeline health across all requisitions.

Active candidates45+12 vs. last quarter

Avg. AI match81%Steady

Hot candidates12Fast follow-up

Interviews YTD119Across all reqs

Activity volume

Recruiting touches per week across all candidates, split by type.

Click a type to focus it

Hiring funnel

Pipeline volume by stage across all reqs. Hover for conversion, click a stage to break down by req.

55 rejected across all stages

Representation goals

Current pipeline representation against org targets.

Women in engineering27% / 32% target
Underrepresented minorities19% / 22% target
International candidates31% / 28% target

Bar is current representation; the tick is the target.

Reqs by priority

P0
4 open reqs
Applied ML · Platform · Research
86 in pipeline
P1
5 open reqs
Product · Product Engineering · Security
80 in pipeline
P2
1 open req
Product Engineering
11 in pipeline

Source mix

Where candidates come from. Hover a slice for its share.

45candidates

Sourced
19 · 42%
Inbound
13 · 29%
Referral
11 · 24%
Rediscovery
2 · 4%
Internal
0 · 0%

AI match quality by req

How well incoming candidates are scoring against req requirements.

Research Engineer, Pre-training
89%
Staff Machine Learning Engineer
87%
Group Product Manager, Platform
84%
Staff Product Designer, Platform
83%
Principal Platform Engineer
82%
Director of Engineering, Platform
81%
Senior Software Engineer, Product
80%
Staff Security Engineer, Application Security
78%
Senior Frontend Engineer, Core
76%
Machine Learning Engineer, Evals
74%