Uber Engineering✓ Add us as a preferred source on Google
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👋 Unclaimed listing — auto-generated from public data; rates are estimates, not set by the creator. 🔒 Paid proposals held safely in escrow — released only when the work's approved.
💰 Suggested sponsorship rate
📊 Post performance
🔥 Top post: 2022 Record Breaking News: Uber’s platform handled a new all tim · 103.2K views
📊 Activity & format
Recent posts
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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
🕵️ Fake follower check
Estimated- 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 ~8.8% typical for this size.
Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.
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🔀 Audience overlap
EstimatedEstimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.
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