Scale AI
Large (~1,200)
Databricks
Large (~7,000)
Best For
Scale AI
Best for: Ambitious builders who want critical AI infrastructure work serving top-tier clients
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Ratings
Scale AIDatabricks
3.5
4.1
Overall
2.7
3.9
Work-Life Balance
2.9
4.0
Culture & Values
3.5
4.3
Comp & Benefits
2.8
3.8
Senior Mgmt
3.6
3.9
Career Opps
👍 56% Recommend
👤 60% CEO Approval (Alexandr Wang)
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
Culture Values
Scale AI only
🚀 Ship Fast & Iterate
Databricks only
💎 Strong Comp & Equity🌈 Diverse & Inclusive
Shared
⚙️ Engineering-Driven🎯 Direct Product Impact🌱 Learning & Growth
Pros & Cons
Scale AI
- Building critical AI data infrastructure used by OpenAI, Meta, Microsoft, and the US government
- Strong compensation for engineers — competitive base + equity
- Work-life balance rated 2.7/5 — long hours common during client deadlines
- Culture and values scored 2.9/5 — inconsistent management quality
Databricks
- Engineers who built Spark, Delta Lake, MLflow — deep technical pedigree
- Strong compensation and equity packages consistently above market
- Hypergrowth means org changes are constant — teams restructure frequently
- Some legacy Spark-era tech debt that can slow down new features
Bottom Line
Scale AI
Choose Scale AI if you want to build data infrastructure for OpenAI and the US government — but expect long hours and inconsistent management.
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Open Roles
Scale AI — 172 jobs
💻 Engineering
51
🧠 ML / AI
26
📋 Product
18
💼 Sales / GTM
11
💰 Finance
8
⚙️ Operations
8
⚖️ Legal
6
📣 Marketing
5
📊 Data
3
👤 HR / People
3
🎨 Design
2
🎧 Support
2
Databricks — 762 jobs
💼 Sales / GTM
292
💻 Engineering
257
📋 Product
51
📊 Data
23
📣 Marketing
15
🧠 ML / AI
15
⚙️ Operations
15
💰 Finance
12
👤 HR / People
9
⚖️ Legal
5
🎨 Design
4