Uber Engineering

Uber Engineering ✓

YouTube @uberengineering Knowledge 📍 United States
Visit YouTube 💰 Sponsor Uber Engineerin… 🤝 Collab with Uber Engineerin… 🎤 Book Event Appearance ⚔ Compare ☆ Watch Own this channel?
Subscribers
24.6K
🔥 Buzz rank
#45,107 ▼32361
Total Views
1.46M
Videos
268
Channel age
10 yrs
Est. monthly earnings
$15 – $29
How we estimate
~3.1K recent monthly views × an estimated ad RPM of $4.90–$9.45 per 1,000 views — adjusted for Knowledge content and a US audience. Yearly ≈ $180 – $348. Excludes sponsorships, memberships & merch. Full methodology →

Known for

Science at Uber: Applying Artificial Intelligence at Uber13.6K views Science at Uber: Applying Artificial Intelligence at Uber Piranha: An Open Source Tool to Automatically Delete Stale Code10.5K views Piranha: An Open Source Tool to Automatically Delete Stale Code [Visualization Nights] Introduction: Kepler.gl & Movement Speeds7.5K views [Visualization Nights] Introduction: Kepler.gl & Movement Speeds Science at Uber: Powering Machine Learning at Uber6.7K views Science at Uber: Powering Machine Learning at Uber

▶️ Featured Video

13.6K views

📈 Performance

Typical video
1.1K–3.9K views
Median 2.2K — the reliable floor a brand can expect, not just the headline average.
Upload rhythm
0.1× / week
Most active on Tuesdays — consistent output keeps an engaged, sponsor-ready audience.
3.1K
Avg views / video
11
Avg likes
0
Avg comments
0.36%
Engagement rate
0.1
Uploads / week
5.4K
Lifetime avg / video
59
Views / subscriber
Engagement rate = (likes + comments) ÷ views across recent videos.

💡 Did you know?

🗓️Joined YouTube in 2016 — 10 years ago.
🏆Ranked #7,041 among all influencers on SocialDB.
🎯Top Knowledge influencer — #432 in the niche.
👁️Averages 3.1K views per video.
📤Posts about 0.1× per week.
💬0.36% engagement rate.
📍Based in United States.

🛡️ Audience credibility

56/100 Fair
  • Est. 73% real, active audience · Medium fake-follower risk.
  • Healthy view-through — roughly 13% of subscribers watch each video.
  • 0.36% engagement — below the ~5% typical for this size.
Est. authentic audience
73%
Fake-follower risk
Medium

Heuristic estimate from view-through, engagement vs size and recent growth — a screening signal, not a guarantee.

👥 Audience demographics

Estimated

Modeled from this creator's niche, platform & region — a planning estimate, not connected analytics.

Gender split
Male 47% Female 53%
Age · peak 18-24
13-178%
18-2432%
25-3431%
35-4416%
45+13%
Top geographies
  • United States46%
  • United Kingdom8%
  • Canada7%
  • Australia4%
  • India5%
Likely interests
EntertainmentLifestyleTrending

💚 Brand affinity

Estimated

Brands Uber Engineering's audience is most likely to respond to — from detected sponsorships in this niche.

Keeps Nebula Amazon Affiliate Patreon Coinbase Robinhood Shopify Webull Audible Brilliant

About

Good things happen when people can move, whether across town or towards their dreams. Tap a button and get to where you want to be.

📸 Gallery

[Uber Open Source] Understanding the History of Apache Pinot [Uber Open Source] Using Apache Pinot at Scale [Uber Open Source] Leveraging Pinot at Uber for Large-scale Analytics [Uber Open Source] New Features in Pinot: Standard SQL and Cloud Readiness Piranha: An Open Source Tool to Automatically Delete Stale Code Introducing Uber's Engineering and Sponsorship Development Program [WiSDOM] Moving the World with Data 2019 Introduction [WiSDOM] Learning Word2Vec Embeddings for Hexcluster Generation

Recent videos

[Uber Open Source] Understanding the History of Apache Pinot
4.9K views · 6 years ago
[Uber Open Source] Using Apache Pinot at Scale
2.9K views · 6 years ago
[Uber Open Source] Leveraging Pinot at Uber for Large-scale Analytics
3K views · 6 years ago
[Uber Open Source] New Features in Pinot: Standard SQL and Cloud Readiness
869 views · 6 years ago
Piranha: An Open Source Tool to Automatically Delete Stale Code
10.5K views · 6 years ago
Introducing Uber's Engineering and Sponsorship Development Program
2.4K views · 6 years ago
[WiSDOM] Moving the World with Data 2019 Introduction
1.8K views · 6 years ago
[WiSDOM] Learning Word2Vec Embeddings for Hexcluster Generation
3.1K views · 6 years ago
[WiSDOM] Conversational AI at Uber
1.2K views · 6 years ago
[WiSDOM] Learning Values and Policies from Observation
882 views · 6 years ago
[Distributed Tracing NYC] Building a DIY Distributed Database in One Weekend
1.9K views · 6 years ago
[Distributed Tracing NYC] Distributed Transactions -- Parallel Commits
1.5K views · 6 years ago

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

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