Software Engineer, AI Platform

Perplexity

$130K — $180K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Strong programming and data engineering skills with proficiency in open source & distributed frameworks (AWS, Spark, Flink, Iceberg, DynamoDB)
  • Familiarity with cloud-based data services (AWS, RDS, DynamoDB) and containerized infrastructure (EKS, Docker)
  • Experience in data streaming (Flink, Spark streaming, CDC)
  • Strong quantitative skills with high-performance estimation experience
  • Background in supporting ML/AI engineering teams for scalable frameworks
  • Self-motivated with ownership of systems and designs
  • 5+ years in distributed systems or AI infrastructure

Responsibilities

  • Collaborate with AI Product and Data Science teams to design and maintain scalable data pipelines
  • Develop high-performance infrastructure for personalization features
  • Create a scalable evaluation platform for various AI products
  • Design tools on foundational infrastructure to enhance personalization and analytics
  • Improve engineering foundations to support product growth and international user base.

Benefits

  • Comprehensive health insurance
  • Flexible working hours
  • Opportunities for professional development
  • Collaborative and dynamic work environment
  • Access to cutting-edge technology and tools
Full Job Description
Perplexity is seeking an experienced Software Engineer focusing on building the next-gen AI Foundation & 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, evaluation and personalization infrastructure and flywheel which powers almost all agent products.

Tech Stack: Spark | AWS Data Stack (S3, RDS, DynamoDB, Docker, EKS, Kinesis) | Pytorch | DynamoDB | Databricks | Snowflake | LLM APIs

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.
Responsibilities
  • Collaborate closely with AI Product, Applied ML, Post-Training, and Data Science teams to design, build, and maintain scalable data pipelines and data lakes
  • Develop high-performance infrastructure that powers personalization features including memory, discover, and agentic products
  • Create a scalable, multi-modal evaluation platform for all Perplexity AI products, including personalization, pro search, labs, deep research, and Comet
  • Design tools and abstractions on foundational infrastructure to enhance personalization, analytics, recommendations, AI products, and post-training capabilities
  • Holistically improve engineering foundation to support rapid growth of Perplexity products and international user base.
Qualifications
  • Strong programming and data engineering skills, with proficiency in open source & distributed framework(AWS, Spark, Flink, Iceberg, DynamoDB)
  • 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 frameworks to accelerate R&D for frontier models and AI products
  • Experience iterating on improving LLM responses and set up proper evaluation framework or Judges to analysis performance holistically.
  • Self-motivated with a strong sense of ownership of systems and designs
  • 5+ years of industry experience in distributed systems or AI infrastructure

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