Perplexity is seeking experienced ML engineers to design, build, and optimize the recommendation systems that power core experiences on Perplexity.
Perplexity builds AI for those who expect more. Our products are designed to help people find answers, make their most consequential decisions, and complete increasingly ambitious work. Across these use cases, the Perplexity experience must feel deeply personal. Great recommendations and user understanding are central to delighting and delivering for each user.
To do this, we are reimagining recommendation systems for the LLM era. Our goal is to combine the intelligence of frontier LLMs, the personalization context that comes from real product usage, and the continual learning capabilities of modern recommendation systems. We build systems that draw on past context and connected data sources to deeply understand each user's needs and recommend the actions that help them get the most out of Perplexity.
Why Perplexity is Different
Our Mission
Perplexity’s mission is to power curiosity. Curious people are the people who drive change in the world. Driving change is a continuous cycle of learning, building, and integrating.
Learn: curious people constantly learn new things by asking more. They question the status quo in their own expertise and they constantly learn outside of it. Research is essential to them and never ending.
Build: curious people make and create things, to show the world their new answers to problems no one else ever questioned. They take action on what they’ve learned. Makers need tools to create their products, their companies, their reality.
Integrate: they must interact with the world as it is to drive change and adoption. True leaders do not simply build something and hope. They must have armies of agents and workers who can constantly work in millions of small ways.
Repeat. For curious people this is a cycle that never ends.
Other benefits are as per company policy.
Work at office
Full time
San Francisco / Palo Alto
Applications for this job are handled on the company's own website.
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