PerplexityRemote
Member of Technical Staff (Software Engineer, Data Flywheel)
United States of America
Full Time
3 weeks ago
H1B Sponsor Likely
Key skills
Software EngineeringPythonSQLBig Data SystemsDistributed ComputeLarge-scale StorageData ModelingSystem DesignDebugging Distributed SystemsAWSLakehouse EcosystemsDatabricksSparkAgentic Coding WorkflowsAI-assisted Development ToolsAIMachine LearningLLMAgenticData Engineering
About this role
Perplexity is a company that serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine. They are seeking a Member of Technical Staff to build the data flywheel that serves teams across the organization, ensuring fast, accurate, and actionable evaluations as the product evolves.
Responsibilities:
- Build the systems and pipelines that enable Search, Product, and other teams to independently access and utilize reliable eval verdicts without bottlenecks
- Take ownership of the "evals-to-product" loop, autonomously determining the best way to turn raw signals into durable datasets that power decision-making across the company
- Build a robust simulator pipeline capable of replaying user interactions with the product in formats legible to LLMs and VLMs, reflecting product changes as they are shipped
- Maintain data trust by implementing monitoring, lineage, and quality checks, ensuring downstream consumers can rely on the results implicitly
- Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality
Requirements:
- 3+ years of software engineering experience shipping production systems
- Strong proficiency in Python and SQL with the ability to write production-grade, maintainable code
- Experience with big data systems including distributed compute and large-scale storage
- Solid fundamentals in data modeling, system design, and debugging distributed systems
- Experience with AWS and lakehouse ecosystems like Databricks or Spark
- Comfortable with agentic coding workflows and using AI-assisted development tools to iterate faster
- Data engineering background including pipelines, orchestration, and warehousing patterns
- Familiarity with LLM/VLM interfaces, tokenization, structured formats, and multimodal payloads
- Experience with evaluation platforms, experimentation systems, or machine learning infrastructure
- Prior work supporting customer-facing products at scale