Lee experiencias reales compartidas por candidatos, incluyendo preguntas, descripción del proceso y señales sobre el nivel de dificultad en OpenAI.
4 experienciasDificultad 5.0/5Technology / AI Research
Member of Technical Staff
virtual
· Dificultad 5/5
Recruiter screen, technical phone, virtual onsite with research/engineering hybrid rounds (one ML, one infra, one safety-thinking), deep-dive on past work, and behavioral. Safety Systems sits between research and product.
Walk me through a safety evaluation you built.
Tell me about discovering a misalignment between training objective and downstream behavior.
Describe collaborating with policy/legal on a deployment decision.
How do you decide what risks are acceptable when shipping a frontier model?
Product Manager
virtual
· Dificultad 5/5
Recruiter screen, hiring manager call, product-sense round on developer experience, analytical (sizing API usage), cross-functional with research, deep-dive, and exec final. API PM at OpenAI works the developer-facing product surface.
Walk me through a launch that moved developer adoption.
Tell me about killing a feature post-launch. Why?
Describe partnering with research on a frontier-model API rollout.
How do you balance API pricing vs. developer accessibility?
Software Engineer
virtual
· Dificultad 5/5
Recruiter screen, two coding rounds, virtual onsite with system design (large-scale chat backend), product-thinking round (improve a ChatGPT feature), deep-dive, and behavioral. Apps team ships consumer-scale ChatGPT.
Tell me about shipping a consumer feature with safety implications.
Describe handling a production incident at huge user scale.
Walk me through how you'd design ChatGPT memory.
How do you balance speed of shipping vs. reliability for an AI product?