AI Infrastructure Engineer, pAGI
OpenAI is seeking a talented AI Infrastructure Engineer to join the pioneering Research department. This role involves designing, building, and optimizing the core infrastructure that powers our cutting-edge research models. You will be instrumental in managing high-scale computational resources, implementing robust networking solutions, and ensuring the elasticity of our distributed systems architecture. Key responsibilities include working with specialized hardware accelerators (like TPUs/GPUs), maintaining CI/CD for infrastructure components, and optimizing resource utilization across cloud environments. The ideal candidate thrives at the intersection of large-scale computing and machine learning, bringing deep knowledge in container orchestration, system reliability engineering, and performance tuning to advance OpenAI's AI frontier.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
Preparing
2500
Question set
150
Duration
Permanent
Focus areas
People Also Ask (FAQs)
What is the last date to apply for AI Infrastructure Engineer, pAGI?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for AI Infrastructure Engineer, pAGI?
Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.
Is there negative marking in the OpenAI test?
The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.
What is the passing marks for this test?
The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.
How can I prepare for the AI Infrastructure Engineer, pAGI test?
Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Cloud Computing, Distributed Systems, Kubernetes, MLOps Infrastructure.
Quick start
Review the job summary, then jump into prep with the same flow used for exam starts.