Lee experiencias reales compartidas por candidatos, incluyendo preguntas, descripción del proceso y señales sobre el nivel de dificultad en Scale AI.
4 experienciasDificultad 3.8/5Technology / AI Data
Operations Manager
virtual
· Dificultad 3/5
Recruiter screen, hiring manager video, case study on a quality-control problem, behavioral, and final with director. Ops at Scale manages large labeling workforce.
Walk me through scaling a labeling operation through customer demand spikes.
Tell me about handling a labeler-quality issue.
Describe partnering with engineering on workflow tooling.
How do you measure labeling quality at scale?
Solutions Engineer
virtual
· Dificultad 4/5
Recruiter screen, hiring manager video, customer scenario architecture, technical Q&A, behavioral, and final with director. SE works with frontier-lab and enterprise customers.
Walk me through scoping a complex labeling engagement.
Tell me about handling a customer-quality dispute.
Describe a deal you advised against. Why?
How do you partner with the AE on a frontier-lab pursuit?
Product Manager
virtual
· Dificultad 4/5
Recruiter screen, hiring manager call, product-sense round on RLHF tooling, analytical, cross-functional, and exec final. GenAI PM works with frontier model labs as customers.
Walk me through partnering with an enterprise customer on RLHF deployment.
Tell me about prioritizing across multiple frontier-lab customers.
Describe partnering with research on annotation-quality metrics.
How do you balance customer-specific needs vs. platform scalability?