Member of Technical Staff (Answer Quality & Evals)

Perplexity

Palo Alto (CA)

On-site

USD 200,000 - 350,000

Full time

3 days ago
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Job summary

Perplexity in Palo Alto is seeking an experienced engineer to advance Answer Quality by building evaluation infrastructure and agent-trace analysis platforms. You will collaborate with data scientists, engineers, and product teams to turn evaluation findings into product improvements.

The role demands 4+ years shipping production systems, strong Python and SQL, and experience with large-scale data processing platforms. This on-site position offers a high-impact, fast-paced environment.

Qualifications

  • 4+ years of software, data, or ML engineering experience shipping and operating production systems.
  • Strong proficiency in Python and SQL, with fundamentals in system design, data modeling, and distributed systems.
  • Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines.

Responsibilities

  • Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product 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

Skills

Python
SQL
Distributed systems
Production systems
Data pipelines
Ownership of projects

Tools

Databricks
Snowflake
ClickHouse

Job description

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.

As our product and agent capabilities evolve, we need evaluation systems that are fast, reliable, production-faithful, and actionable. In this role, you will build and improve the technical foundations that support Answer Quality across Perplexity. This includes our shared evaluation infrastructure and the platform used to replay and analyze agent traces. You will work closely with data scientists, engineers, and product teams to identify quality problems, measure their impact, and turn evaluation findings into product improvements.

Responsibilities
  • 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
Qualifications
  • 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
Preferred Qualifications
  • 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

Compensation Range: $200K - $350K

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