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Member of Technical Staff (Software Engineer, Applied AI)

Perplexity · San Francisco

Overview

You will design and build autonomous AI agents and context layers for millions of users on the core Perplexity product team.

Skills

PythonLLMsRAGPersonalizationA/B TestingAgents

Responsibilities

  • Build LLM personalization and context layers
  • Develop frontier agent capabilities for Perplexity Computer
  • Design online and offline research harnesses and metrics
  • Own the full model lifecycle from research to production
  • Run A/B tests and iterate on agent performance

Requirements

  • 5+ years building and shipping robust AI products
  • Strong software engineering skills in Python
  • Experience with the full AI lifecycle and evaluation
  • Degree in Computer Science, Engineering, or related field
Nice to have
  • Experience with LLM context or harness engineering
  • Experience in mid-training or post-training open source models
  • Experience in large scale personalization and ranking

About Perplexity

Perplexity builds an AI-powered search and answer engine.

What to prepare

Agent architectureContext engineeringAI evaluationRetrieval and ranking
Summarised by AI from the job post. Check the full post before applying.
Full job post · as written by Perplexity

Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our core experience in Perplexity Computer. Working in this mission critical team, you will develop frontier context layer applications - fulfilling the curiosity of millions of users across the globe.

Key Responsibilities

  • Apply state-of-the-art ML and LLM techniques to solve problems spanning:
  • Personalization (LLM memory, context summarization, retrieval and ranking);
  • Contextual recommendations and Monetization applications
  • Build frontier agent capabilities on top of Perplexity Computer
  • Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact.
  • Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces.
  • Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements.
  • Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle.

Preferred Qualifications

  • 5+ years experience building and shipping robust AI products for large-scale, user-facing or data-driven products.
  • Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large scale parallel developments.
  • In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement.
  • Proven collaborator and communicator; excels in high-velocity, cross-functional teams.
  • Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI.
  • BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience).

Bonus Points For

  • Experience with LLM context engineering or harness engineering.
  • Experience in mid-training or post-training frontier open source models
  • Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc).