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Perplexity

Member of Technical Staff (Answer Quality & Evals)

San FranciscoEnglish$200k–350k
EngineeringAI & DataResearchAITechnology
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At a glance
LocationSan Francisco
Work styleNot specified
TypeNot specified
ScheduleNot specified
Remuneration$200k–350k
Start datePerplexity serves tens of millions of users daily with reliable,…
DeadlineNot stated
Required languagesNot stated
The opportunity

About the role

Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search systems, datasets, and models work together to create the best possible experience for our users.

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Your work

What you’ll do

  • Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product and model decisions
  • Develop the platform for replaying and analyzing agent traces to reproduce production behavior and diagnose failures
  • Build and operate scalable systems for processing, storing, and monitoring interaction, trace, and evaluation data
  • Partner with data scientists, engineers, and product teams to turn answer-quality problems into evaluations, analyses, and product improvements
  • Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality
What matters

What they’re looking for

Select a requirement to inspect fit, evidence or application context.

  • 4+ years of software, data, or machine learning engineering experience shipping and operating production systems
  • Strong proficiency in Python and SQL, with solid fundamentals in system design, data modeling, and distributed systems
  • Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines
  • Demonstrated ownership of ambiguous technical projects from initial design through production operation
  • Ability to work effectively with data scientists, engineers, and product partners

Helpful, not always essential

  • Experience building evaluation, experimentation, observability, or machine learning infrastructure
  • Familiarity with LLM and agent systems, including tool use, execution traces, replay, and simulation
  • Experience building on top of large-scale data processing platforms such as Databricks, Snowflake, or ClickHouse
The organization

About Perplexity

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