Member of Technical Staff (Data Scientist, Evals)

at Perplexity AI

📍 San Francisco, United States

USD 200,000-300,000 per year

MIDDLE SENIOR

✅ Hybrid

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 AWS @ 3 Data Science @ 5 Databricks @ 3 LLM @ 3 Machine Learning @ 5 Python @ 6 SQL @ 6 Technical Leadership

Details

Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and our specialized data sources. We aim to use the latest models as they are released, but the intelligence frontier is a jagged one, and popular benchmarks do not effectively cover our use cases. In this role, you will build specialized evals to improve answer quality across Perplexity, covering search-based LLM answers and other scenarios popular with our users.

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

Benefits

Full-time U.S. employees enjoy a comprehensive benefits program including equity, health, dental, vision, retirement, fitness, commuter and dependent care accounts, and more.
Full-time employees outside the U.S. enjoy a comprehensive benefits program tailored to their region of residence.
USD salary ranges apply only to U.S.-based positions. International salaries are set based on the local market. Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.