Anyscale
Medium (~250)
Labelbox
Medium (~350)
Best For
Anyscale
Best for: Distributed systems and ML infrastructure engineers who want to work on the Ray open-source project and commercial AI infra
Labelbox
Best for: ML infrastructure engineers building data labeling and training platforms for frontier AI labs and enterprises
Ratings
AnyscaleLabelbox
4.2
3.8
Overall
3.8
3.6
Work-Life Balance
4.2
3.8
Culture & Values
4.1
3.6
Comp & Benefits
4.0
3.5
Senior Mgmt
4.0
3.6
Career Opps
👍 84% Recommend
👤 87% CEO Approval (Robert Nishihara)
👍 72% Recommend
👤 78% CEO Approval (Manu Sharma)
Culture Values
Anyscale only
🔓 Open Source🤝 Flat Hierarchy
Labelbox only
💎 Strong Comp & Equity🌈 Diverse & Inclusive
Shared
⚙️ Engineering-Driven🚀 Ship Fast & Iterate
Pros & Cons
Anyscale
- Brilliant colleagues from top companies
- Direct impact on AI/ML ecosystem
- Context switching between projects
- Documentation can lag behind development
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
Anyscale
Choose Anyscale if you want to work on Ray — the dominant compute framework for AI workloads — with strong engineering culture and open-source DNA.
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
Anyscale
No open roles currently listed
Labelbox — 9 jobs
💻 Engineering
3
🧠 ML / AI
3
📊 Data
1
Summary
Anyscale scores 4.2/5.0 on Glassdoor with a 3.8 work-life balance rating. Labelbox scores 3.8/5.0 overall with a 3.6 WLB. That’s a 0.4-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Ship Fast & Iterate. Anyscale also emphasizes Open Source, Flat Hierarchy. Labelbox also emphasizes Strong Comp & Equity, Diverse & Inclusive.
On the hiring front, Anyscale has 0 open roles and Labelbox has 9 open roles.