Databricks
Large (~7,000)
Scale AI
Large (~1,200)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Scale AI
Best for: Ambitious builders who want critical AI infrastructure work serving top-tier clients
Ratings
DatabricksScale AI
4.1
3.5
Overall
3.9
2.7
Work-Life Balance
4.0
2.9
Culture & Values
4.3
3.5
Comp & Benefits
3.8
2.8
Senior Mgmt
3.9
3.6
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 56% Recommend
👤 60% CEO Approval (Alexandr Wang)
Culture Values
Databricks only
💎 Strong Comp & Equity🌈 Diverse & Inclusive
Scale AI only
🚀 Ship Fast & Iterate
Shared
⚙️ Engineering-Driven🌱 Learning & Growth🎯 Direct Product Impact
Pros & Cons
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
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
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
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.
Open Roles
Databricks — 789 jobs
💼 Sales / GTM
319
💻 Engineering
258
📋 Product
52
📊 Data
23
⚙️ Operations
17
🧠 ML / AI
15
💰 Finance
12
📣 Marketing
11
👤 HR / People
9
⚖️ Legal
5
🎨 Design
4
🎧 Support
1
Scale AI — 169 jobs
💻 Engineering
52
🧠 ML / AI
26
📋 Product
17
⚙️ Operations
9
💼 Sales / GTM
9
💰 Finance
8
⚖️ Legal
7
📣 Marketing
5
📊 Data
4
👤 HR / People
3
🎨 Design
2
🎧 Support
1