Member of Technical Staff

Responsibilities

• Architect and maintain automated evaluation pipelines to assess answer quality across Perplexity's products, ensuring high standards for accuracy and helpfulness.
• Design evaluation sets and methods specifically to measure the impact of tool calls (particularly web search retrieval) on the final answer's quality.
• Develop VLM-based solutions to programmatically evaluate how final answers render visually across different platforms and devices.
• Continuously review public benchmarks and academic evaluations for their applicability to the Perplexity product, adapting and incorporating them into our regular performance measurements.
• Operate within a small, high-impact team where your evaluation metrics directly shape product changes, collaborating closely with technical leadership to measure and improve Answer Quality.

Requirements

• PhD or MS in a technical field or equivalent experience.
• 4+ years of experience in data science or machine learning.
• Strong proficiency in Python and SQL (expected to write production-grade code).
• Experience building within a modern cloud data stack, specifically AWS and Databricks.
• Comfortable with agentic coding workflows and using AI-assisted development tools to iterate faster.

Preferred Qualifications

• 1+ years of experience working with LLMs at scale, specifically with LLM-as-a-judge setups.
• Prior experience working on customer-facing web products or consumer apps, with real user traffic at scale.
• A strong research background, with experience applying research methods to real-world ML problems.
• Experience defining evaluation metrics (e.g., factual consistency, hallucination rate, retrieval precision) and building ground truth datasets.