Member of Technical Staff (Software Engineer, Applied AI)

Stack

Responsibilities

• ▹Apply state-of-the-art ML and LLM techniques to personalization (LLM memory, context summarization, retrieval and ranking), contextual recommendations, and monetization applications
• ▹Build frontier agent capabilities on top of Perplexity Computer
• ▹Build an auto research harness for offline and online techniques, designing experiments and metrics for quality and impact insight
• ▹Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, iterative improvement, and autonomous harness for agent squads
• ▹Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure AI drives meaningful product improvements
• ▹Stay at the forefront of ML/AI innovation, incorporating emerging research and algorithms into the product lifecycle

Requirements

• ▹5+ years of experience building and shipping robust AI products for large-scale, user-facing or data-driven products
• ▹Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience with agentic coding tools for large-scale parallel development
• ▹In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, ongoing monitoring/improvement
• ▹Proven collaborator and communicator, excelling in high-velocity, cross-functional teams
• ▹Curious, product-impact driven, passionate about advancing applied ML and AI
• ▹BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience)

Nice to have

• ▹Experience with LLM context engineering or harness engineering
• ▹Experience in mid-training or post-training frontier open source models
• ▹Experience in large-scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking)

Soft skills

About the company

Perplexity's Applied AI team builds cutting-edge agents powering Computer's core experience, serving the curiosity of millions of users globally.