Design, implement, and maintain critical components of a large-scale search engine while optimizing performance, scalability, and efficiency using cloud tools.

Develop and enhance AI-driven discovery products by integrating various content sources, and optimize recommendation systems with machine learning models.

The AI Machine Learning Engineer will architect and build personalization models for user experience, involving DNN and LLM technologies, while collaborating with product managers to deliver high-quality outputs.

As the first Analytics Engineer, design and build analytics infrastructure, ensuring data reliability and accessibility to drive business decisions. Collaborate on data modeling and dashboard creation while leading data governance efforts.

The Revenue Accounting Manager will establish revenue recognition policies, assist in system implementations, support financial reporting, and ensure compliance with accounting principles.

The Growth Manager will drive feature launches and product marketing, working with cross-functional teams to enhance user engagement and product accessibility.

The role involves leading the APAC Customer Success team, scaling operations in Tokyo, developing engagement strategies, and improving support efficiency while collaborating with various departments.

Design and implement core search components, optimize data subsystems for analytics, and improve system performance through JVM tuning.

Join the Search Core team as a Senior C++ Developer to build advanced search products, focusing on architecture, development, and optimization processes in a high-load environment.

Develop insights from user behavior, run A/B tests, track metrics with dashboards, and implement data pipelines for search improvement.

Build and implement a comprehensive post-training framework for large language models with a focus on scaling and integration into products.

The backend engineer will design, implement, and scale systems for API products, ensuring infrastructure meets user needs and supporting growth initiatives.

The Customer Success Engineer will provide technical support and guidance to enterprise customers, focusing on troubleshooting and improving product usage through collaboration with internal teams.

The AI Inference Engineer will develop APIs for AI inference, benchmark and optimize the inference stack, improve system reliability, and explore LLM inference optimizations. They will engage in large-scale deployment of machine learning models for real-time usage.

Join the team to develop APIs for AI inference, benchmark systems, improve reliability, and optimize LLM implementations.

The Data Scientist will develop insights from user behavior, validate hypotheses through A/B testing, and build dashboards to track product metrics, collaborating with various teams to shape the product direction.

The Developer Experience Engineer will design and maintain developer environments, optimize CI/CD processes, and enhance workflows for the development team.

The Site Reliability Engineer will design, implement, and scale infrastructure for web and mobile products, ensuring performance and reliability.

Lead product feature launches and user communication strategies at Perplexity, focusing on marketing and user engagement in the AI sector.

The Full Stack AI Software Engineer will propose product features with LLMs, improve code quality, and collaborate with various teams to enhance product delivery.