Member of Technical Staff (Software Engineer, AI Platform)
Résumé du poste par JobGrid
Member of Technical Staff (Software Engineer, AI Platform) at Perplexity: San Francisco, États-Unis; Sur site. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: San Francisco, États-Unis, Sur site
- Source freshness: checked by JobGrid on 2026-05-28.
- Application path: candidates continue to the employer application page with non-personal referral tags.
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