Databricks
Large (~7,000)
Labelbox
Medium (~350)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Labelbox
Best for: ML infrastructure engineers building data labeling and training platforms for frontier AI labs and enterprises
Ratings
DatabricksLabelbox
4.1
3.8
Overall
3.9
3.6
Work-Life Balance
4.0
3.8
Culture & Values
4.3
3.6
Comp & Benefits
3.8
3.5
Senior Mgmt
3.9
3.6
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 72% Recommend
👤 78% CEO Approval (Manu Sharma)
Culture Values
Databricks only
🌱 Learning & Growth🎯 Direct Product Impact
Labelbox only
🚀 Ship Fast & Iterate
Shared
⚙️ Engineering-Driven💎 Strong Comp & Equity🌈 Diverse & Inclusive
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
Labelbox
- Competitive compensation and equity
- Working with top AI labs as customers
- Rapid growth creates organizational churn
- Some teams move faster than others
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Labelbox
Choose Labelbox if you want to work on the data side of AI — labeling, evaluation, and training infrastructure used by frontier AI teams — with moderate SF-based intensity.
Open Roles
Databricks — 842 jobs
💼 Sales / GTM
353
💻 Engineering
284
📋 Product
39
📣 Marketing
34
📊 Data
22
👤 HR / People
12
🧠 ML / AI
12
⚙️ Operations
11
🎨 Design
6
💰 Finance
5
⚖️ Legal
5
Labelbox — 9 jobs
💻 Engineering
3
🧠 ML / AI
3
📊 Data
1
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Labelbox scores 3.8/5.0 overall with a 3.6 WLB. That’s a 0.3-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Strong Comp & Equity, Diverse & Inclusive. Databricks also emphasizes Learning & Growth, Direct Product Impact. Labelbox also emphasizes Ship Fast & Iterate.
On the hiring front, Databricks has 842 open roles and Labelbox has 9 open roles.