Member of Data Staff (Data Acceleration)
San Francisco • FullTime
Posted 1mo ago
About the job
Perplexity is seeking a highly experienced individual to join their data team, focusing on building AI systems that fundamentally change how data science is performed. This role involves creating AI agents and internal systems capable of handling end-to-end analysis workflows, from hypothesis formation to drafting recommendations. You will also develop the retrieval infrastructure, evaluation loops, and automated workflows necessary for reliable AI-driven data analysis and issue resolution. The goal is to transform existing AI-assisted workflows into scalable, shared tools and establish an AI-native operating model for the data team.
Responsibilities
- Build AI agents to perform data science tasks, including data exploration, hypothesis formation, query execution, result interpretation, and recommendation generation with evaluation and review loops.
- Develop retrieval infrastructure and evaluation loops to enable AI systems to reliably query warehouse data using semantic context and metadata.
- Transform existing AI-assisted workflows into repeatable systems, reusable tools, and adoption patterns for the data team.
- Automate the data lifecycle through self-healing pipelines, automated dbt model generation and validation, and data quality agents.
- Build agents to interpret A/B test results, identify statistical issues, pinpoint drivers, and draft ship/no-ship recommendations.
- Develop internal data products and self-serve AI interfaces to replace ad hoc requests.
- Own the full lifecycle of AI systems, from identifying problems and prototyping to production deployment and quality monitoring.
Requirements
- 6+ years of experience in data science, analytics engineering, data engineering, or a related field.
- Deep understanding of SQL and strong analytical judgment for metrics, experiments, and data models.
- Strong product sense to understand stakeholder needs and create adoptable workflows.
- Production-oriented Python skills for building tools, managing APIs, evaluating models, and deploying services.
- Hands-on experience with LLMs, agents, RAG systems, evaluations, or AI-powered workflows.
- Fluency in pipeline development and data modeling, including experience with dbt, warehouse schemas, and data quality.
- A builder mentality focused on systematizing manual processes and iterating based on quality metrics.
- Ability to work autonomously and contribute to defining the roadmap for a new function.
Benefits
- Opportunity to set industry standards for AI in data teams.
- Access to frontier AI infrastructure and expertise.
- Massive leverage through building systems that multiply team output.
- Direct impact with a small team and rapid idea-to-ship cycles.