Are these based on real engineering roles?
Yes. The catalog is built around real engineering role patterns so the practice round feels closer to a live interview.
Company practice
Perplexity mock interviews
Pick a role, answer follow-up questions out loud, and get a scored verdict after the interview.
4 rolesPythonTypeScriptAWSCUDA
Create custom interviewRoles to practice
Perplexity
ML / AI
AI Inference Engineer (Member of Technical Staff)
Build and run the inference engine behind every Perplexity query, writing high-performance kernels and serving infrastructure that keeps answer latency low at search-engine scale. The stack is Rust, Python, CUDA, and CuTe DSL, with a focus on squeezing maximum throughput out of each GPU. A technical interview would probe GPU kernel optimization, attention and KV-cache implementation details, and how you'd profile and eliminate bottlenecks in a continuous-batching inference server.
RustCUDAPythonPerplexity
Infrastructure
AI Infrastructure Engineer (Member of Technical Staff)
Build and operate the large-scale compute and orchestration platform that powers Perplexity's training and serving workloads, working with Kubernetes, Slurm, PyTorch, and primarily AWS. You'll manage GPU clusters, job scheduling, and the reliability of infrastructure shared across research and product teams. A technical interview would probe distributed training infrastructure, container and cluster orchestration at scale, and how you'd debug a multi-node GPU job that's bottlenecked on networking or scheduling.
KubernetesPyTorchSlurmPerplexity
ML / AI
AI Software Engineer - Comet Agents
Build the agentic experiences inside Perplexity's Comet browser, creating AI agents that autonomously navigate and act on the web using context engineering, tool interfaces, and browser automation (CDP, Playwright, extensions). You'll work across AI/ML, backend, and full-stack with a high bar on both agent performance and user experience. A technical interview would probe context-window and tool-calling design for frontier models, browser-automation reliability, and how you'd evaluate and harden a web-navigating agent against flaky, adversarial pages.
PythonTypeScriptPlaywrightPerplexity
Fullstack
Full Stack Software Engineer - Applied AI
Build end-to-end AI product features spanning discovery, research agents, evaluation platforms, and monetization, integrating Perplexity's Sonar LLMs and third-party models into polished user-facing experiences. You'll move across frontend, backend, and the model-integration layer to ship complete products. A technical interview would probe full-stack system design, streaming LLM responses to a responsive UI, and how you'd structure an evaluation pipeline to measure and improve an AI feature in production.
TypeScriptReactPython
ExoForm is not affiliated with Perplexity. This is an independent practice page.
FAQ
Is the interview voice-based?
Yes. ExoForm runs a live voice interview, asks follow-ups, and produces structured feedback after the session.
Can I try it for free?
Yes. You can start with the free interview allowance before upgrading for more practice.