Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world's leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world's most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that's growing rapidly for one simple reason: everyone can be curious. Perplexity is seeking an experienced Software Engineer focusing on building the next-gen AI Data Platform to help revolutionize the way people search and interact online. In this role, you'll help build Perplexity's end-to-end AI data stack and flywheel which powers all AI products, ML use cases and language models. Perplexity is rapidly scaling both in number of use cases and number of users. Perplexity's data stack powers scalable, personalized and fast answers for millions of people worldwide. Tech Stack: Spark | AWS Data Stack (S3, RDS, DynamoDB, Docker, EKS, Kinesis) | Pytorch | Docker | Databricks | Snowflake Responsibilities Collaborating closely with AI Product, Applied ML, Post-Training and Data Science teams to design, build, and maintain scalable data pipelines and data lakes Developing, deploying, and monitoring entire data lifecycle for ingestion, transformation, streaming and storage at high scale Implementing tools and abstractions on top of data infrastructure for a variety of analytics, recommendations, AI product and post-training use cases Working closely with product and AI teams to develop reusable data resources and design patterns Qualifications Extensive programming and data engineering skills, with proficiency in open source & distributed data processing (AWS, Spark, Flink, Iceberg) Familiarity with cloud-based data services (e.g., AWS, RDS, DynamoDB), containerized infrastructure (e.g., EKS, Docker), and data streaming (Flink, Spark streaming, CDC Strong quantitative and engineering skills with experience in estimating performance at high scale Experience supporting various ML/AI engineering teams to build scalable platforms to accelerate R&D for frontier models and AI products Self-motivated with a strong sense of ownership of systems and designs 5+ years of industry experience in distributed systems or AI infrastructure The cash compensation range for this role is $200,000 - $280,000.

Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.

Equity: In addition to the base salary, equity may be part of the total compensation package. Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.