Meta Coding for Infra interview questions
Meta’s Llama 3 report describes large distributed training runs and their interruptions. Use that operational setting for a systems-coding exercise, without treating it as a published Meta interview question. Questions tagged to Meta appear first, followed by additional practice from our Coding for Infra track. Company tags indicate preparation relevance, not confirmed interview appearances. Confirm the current interview format with your recruiter.
Implement a failure detector with explicit uncertainty
- Track observed state. Maintain worker identifiers, heartbeat times and a timeout using a monotonic clock. Distinguish an unreachable worker from proof that its process has stopped.
- Prevent duplicate ownership. Model a late heartbeat after replacement and a delayed result from the old worker. Require an ownership generation or equivalent fencing rule before accepting updates, then test expiry and reassignment at the same instant.
Sources: Meta: The Llama 3 Herd of Models. Reviewed .
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Coding for Infra questions tagged to Meta
Additional Coding for Infra practice
These questions cover the same topic and are not tagged to Meta. Use them to practise applying the ideas in a different situation.
Concepts for Coding for Infra preparation
These concept explanations cover the ideas used in the questions. Check each card for its access level.
This collection includes practice questions such as "Given per-rank heartbeats from a training job, detect which rank has stopped and when. What produces false positives?", "Implement dominant resource fairness for a cluster where jobs need different mixes of GPU, CPU and memory.", "A multi-GPU training job hangs at step 400 with every GPU at 100 percent utilization. Debug it.". Company tags describe relevance to preparation; they do not confirm that Meta asked these questions. Check each question for answer access.
Start with a question at your level, use the linked concepts to understand the mechanism, then practise explaining your decision and its limits. Review the company guide's sources and confidence notes, and confirm the current role and interview format with your recruiter.
Yes: Software Engineer, Systems ML (E4 to E5 postings in 2026 covering AI infra, hardware acceleration and benchmarks), Research Engineer, Production Engineer for AI infrastructure, and infrastructure roles inside Meta Superintelligence Labs.
Documented SWE and MLE loop: a recruiter screen, a 45-minute coding screen, then up to six 45-minute rounds: two coding (one of which may be the AI-enabled round), ML system design and sometimes infra design, and behavioral. Production Engineer loops (first-hand 2025 debrief): a screen with a file-parsing task, an easy string problem and a troubleshooting exercise; an onsite of coding with optimization follow-ups, PE system design, a Linux round (memory, processes, filesystems, security, networking) and behavioral.
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