Member of Technical Staff (Model Behavior)
Perplexity·Palo Alto, California, United States | San Francisco, California, United States$200K - $330K·posted 16d ago · last seen 51m agoTrack this application
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Get Started FreeAbout interviewing at Perplexity
One of the few AI startups with a fully published interview guide (perplexity.ai/hub/careers/interview-guide): online application (response within two weeks) → recruiter phone screen → a technical screen that for engineers is 'usually a standard technical programming interview' → a quickly-scheduled onsite of 4–5 interviews including a hiring-manager deep dive on past work and experience anecdotes → a final interview with a Perplexity founder or leader → decision within a week of the onsite. Coding leans Python and mixes LeetCode medium–hard with practical search-flavored tasks (ranking/filtering, concurrency, data handling); system design is AI-native (RAG pipelines, retrieval at scale, LLM serving cost/latency). Applicants are judged 'solely on merit and potential impact' and must show 'frontier knowledge and excellence in at least one area'; roles are broad by default with team matching happening during the onsite, every role — managers included — is hands-on, and building AI products isn't expected but fluency in using AI tools is required. In-person 4 days/week near an office; remote is case-by-case.
Read the full Perplexity interview process →Description
About the Role
We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models.
The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products.
What you'll do
Context Engineering: Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases. Build self-improvement loops to steer the prompt, improve tool/skill use, and improve the ability to draw on memory.
Model Releases: Help experiment with and release new models.
Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects, for both internal and production systems.
Knowledge Sharing: Help engineers across teams build intuition for prompt design and context engineering best practices.
Staying Current: Track the latest prompting, context engineering, and alignment techniques from industry and academia, and bring the best ideas back to the team.
What We're Looking For
Required
2 to 10+ years of experience in software engineering or research.
Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems.
Experience shaping LLM behavior through prompts, tool and skill design, or memory systems.
Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.
Nice to have
Recent experience working on modern LLM-driven products.
Experience working across teams or with external partners.
Experience designing evaluations or benchmarks for AI systems.
Salary Range: $200K - $330K
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