Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering their core experience in Perplexity Computer. In this role, you will apply state-of-the-art ML and LLM techniques to develop applications that enhance user experience and drive product improvements.
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
Requirements:
- 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
- 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)
- 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)