Member of Technical Staff (Software Engineer, Applied AI) at Perplexity (San Francisco, CA)
Perplexity· San Francisco, CA· $220k–$405k·
Role details
Equity
Perplexity at a glance
AI-powered answer engine that returns real-time, cited answers, now expanding into an agentic browser and on-device agents.
Perplexity runs an AI answer engine that searches the live web and returns direct, cited answers instead of a page of links. It has extended that core into an AI browser (Comet), an on-device agent (Computer), a developer API, and vertical tools like patent search.
$1.7B raised · latest: Series E extension · $200M · 2025 (reported $20B valuation) · backed by Accel, IVP, NEA, SoftBank Vision Fund 2
Summary
Design, build, and iterate on cutting-edge agents powering Perplexity Computer's core experience. Develop frontier context layer applications using state-of-the-art ML and LLM techniques to fulfill user curiosity and drive product improvements.
Job description
Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our core experience in Perplexity Computer. Working in this mission critical team, you will develop frontier context layer applications - fulfilling the curiosity of millions of users across the globe.
Key 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.
Preferred Qualifications
- 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).
Bonus Points For
- 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).
Why work at Perplexity
- Culture & Environment: “Thoughtful support” culture with emphasis on craftsmanship, ownership, entrepreneurship, scholarship, and partnership. Hybrid schedule (4 days in-office) based on location.
- Perks: Daily catered meals (breakfast, lunch, dinner in office), office snacks, ride home program, commuter benefits, home office reimbursement, fitness classes, gym memberships.
- Compensation & Benefits: Competitive salary and equity packages; retirement plans with company match; flexible PTO; holiday shutdown between Christmas and New Year; 12 weeks paid bonding leave; comprehensive health, dental, and vision insurance.
- Relocation & Visa Support: Relocation assistance and visa/green card sponsorship for eligible roles. Partners with immigration firm to support the process.
- Engineering Excellence: “Technical assessment for relevant roles”; values hands-on contribution, broad skill sets, and merit-based evaluation. Frequent Tech Talks and exposure to greenfield AI research problems.