Member of Technical Staff (Software Engineer, Applied AI)
Perplexity
- Location
- United States
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 220,000–405,000/yr
Posted 28d ago
Note
The job is a remote job and is open to candidates in USA. Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering their core experience in Perplexity Computer. In this role, you will apply state-of-the-art ML and LLM techniques to develop applications that enhance user experience and drive product improvements.
Responsibilities
- Apply state-of-the-art ML and LLM techniques to solve problems spanning:
- Personalization (LLM memory, context summarization, retrieval and ranking)
- Contextual recommendations and Monetization applications
- Build frontier agent capabilities on top of Perplexity Computer
- Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact
- Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces
- Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements
- Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle
Skills
- Apply state-of-the-art ML and LLM techniques to solve problems spanning: Personalization (LLM memory, context summarization, retrieval and ranking); Contextual recommendations and Monetization applications; Build frontier agent capabilities on top of Perplexity Computer
- Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact
- Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces
- Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements
- Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle
- 5+ years 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 using agentic coding tools for large scale parallel developments
- In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement
- Proven collaborator and communicator; excels in high-velocity, cross-functional teams
- Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI
- BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience)
- 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, etc)
Company Overview
- Perplexity is an AI-powered platform that retrieves, analyzes information from the web to deliver structured answers with cited sources. It was founded in 2022, and is headquartered in San Francisco, California, USA, with a workforce of 201-500 employees. Its website is https://www.perplexity.ai.
Company H1B Sponsorship
- Perplexity has a track record of offering H1B sponsorships, with 10 in 2026, 11 in 2025, 7 in 2024, 2 in 2023. Please note that this does not guarantee sponsorship for this specific role.
Skills
- AI
- Machine Learning
- LLM
- Python
- Agentic Coding Tools
- Data Analysis
- Model Evaluation
- A/B Testing
- Personalization
- Context Engineering
- Harness Engineering
- User Modeling
- Retrieval
- Content Ranking
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