🤝
Make a deal with Uber Engineering
🔒 Paid proposals held safely in escrow — released only when the work's approved.
Followers
59.1K
Posts
11.5K
Following
5.4K
Account age
12 yrs
💰 Suggested sponsorship rate
$331 – $538 / sponsored post
Estimated from audience size & typical reach — every deal is negotiable and held in SocialDB escrow.
🧰 Free analysis for Uber Engineering
📊 Post performance
73.9K
Avg views / post
1.2×
Reach vs followers
Jun 2014
On X since
🔥 Top post: 2022 Record Breaking News: Uber’s platform handled a new all tim · 103.2K views
📊 Activity & format
Posting cadence
0.05 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly images
Recent: 2 video · 8 image · 8 text.
Follower / following
11×
Follows 5.4K back. A strong ratio — an audience that follows them, not a follow-for-follow network.
Verification
✓ X Premium
A paid X Premium (Blue) verified account.
Recent posts
View on X ↗
Eager to explore arm64 on servers, but stuck on an infrastructure that assumes one architecture? That’s where Uber was 18 months ago. In this blog post we explain how we bootstrapped arm64 infrastructure using a relatively new toolchain in…
New on our blog today! Members of our engineering team describe how we reduced the code size of Uber’s iOS Rider app by using advanced compiler technologies.
read more:
New on our blog today! Members of our engineering team introducing generalized approach to microservice architectures, Domain-Oriented Microservice Architecture (DOMA). #architecture
read more:
▶
Designed by @Uber's Office of the CTO, the Engineering Sponsorship and Development Program pairs participants with sponsors and provides an opportunity to hone technical leadership skills.
https://t.co/NkWom1PWro
#Mentorship #DiversityIncl…
Architecting our driver app for Android, which needs to run for extended periods of time in the background, involved a unique idea where Activities and Services were not included in the structural foundations.
▶
With the release of https://t.co/2j6MbIKW4S version 7.3, @Uber’s open source visualization tool now supports rendering massive geospatial data sets formatted according to the OGC 3D Tiles community standard.
https://t.co/kzKF93sjiB
New on the blog today:
'I thought it was so cool that you could combine the ideas behind evolution and use them to automatically design complex things that can then impact the real world.' - @jeffclune, Senior Research Manager, Uber AI Lab…
To determine if it made sense to adopt Kotlin for Uber's #Android monorepo, our Mobile Engineering team, in collaboration with @jetbrains, measured #Kotlin build performance at scale across a variety of project structures.
Read the artic…
Out today: Uber #AI introduces Ludwig, an #OpenSource, #DeepLearning toolbox built on top of @TensorFlow that allows users to train and test deep learning models without writing code.
Read the article: https://t.co/31Q2VcwdZY
Check out …
Out today: introducing Manifold, Uber's model-agnostic visual debugging tool for #MachineLearning at Uber
Read the article: https://t.co/xMrIBVhlND via @lezhili & @gnavvy
Learn more about Uber's #DataVisualization team: https://t.c…
Out now: Uber #AI introduces a new approach for making #NeuralNetworks process images faster & more accurately with #JPEG representations.
https://t.co/XZjccsM5Rh via Lionel Gueguen @alsrgv @savvyRL & @jasonyo
Check out the res…
▶
Designed by @Uber's Office of the CTO, the Engineering Sponsorship and Development Program pairs participants with sponsors and provides an opportunity to hone technical leadership skills.
https://t.co/NkWom1PWro
#Mentorship #DiversityIncl…
Architecting our driver app for Android, which needs to run for extended periods of time in the background, involved a unique idea where Activities and Services were not included in the structural foundations.
▶
With the release of https://t.co/2j6MbIKW4S version 7.3, @Uber’s open source visualization tool now supports rendering massive geospatial data sets formatted according to the OGC 3D Tiles community standard.
https://t.co/kzKF93sjiB
New on the blog today:
'I thought it was so cool that you could combine the ideas behind evolution and use them to automatically design complex things that can then impact the real world.' - @jeffclune, Senior Research Manager, Uber AI Lab…
To determine if it made sense to adopt Kotlin for Uber's #Android monorepo, our Mobile Engineering team, in collaboration with @jetbrains, measured #Kotlin build performance at scale across a variety of project structures.
Read the artic…
Out today: Uber #AI introduces Ludwig, an #OpenSource, #DeepLearning toolbox built on top of @TensorFlow that allows users to train and test deep learning models without writing code.
Read the article: https://t.co/31Q2VcwdZY
Check out …
Out today: introducing Manifold, Uber's model-agnostic visual debugging tool for #MachineLearning at Uber
Read the article: https://t.co/xMrIBVhlND via @lezhili & @gnavvy
Learn more about Uber's #DataVisualization team: https://t.c…
Out now: Uber #AI introduces a new approach for making #NeuralNetworks process images faster & more accurately with #JPEG representations.
https://t.co/XZjccsM5Rh via Lionel Gueguen @alsrgv @savvyRL & @jasonyo
Check out the res…
💡 Facts
🗓️Joined X in 2014 — 12 years ago.
👁️Averages 73.9K views per post.
📤Posts about 0.1× per week.
💬0.57% engagement rate.
🏅Earned the 10K Followers for passing 10K followers.
🛡️ Audience credibility
69/100
Good
Credibility score
85%
Real
Real audience
Low
Fake-follower risk
High
Data confidence
- Est. 85% real, active audience · Low fake-follower risk.
- Engagement (~1.2× of followers engage each post) is around typical for X.
- Organic base — far more followers than accounts it follows.
- Verified account.
- Established account (12+ years old).
- 0.57% engagement — below the ~18% typical for this size.
Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.
About
Engineering @Uber, from practice to people.
http://eng.uber.com ✨
📸 Gallery
🔀 Audience overlap
EstimatedEstimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.
The Linux Foundation
17%
boardzy
16%
Shu
14%
ZETA aco
12%
Albinder Dhindsa
10%
UK House of Commons
10%
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