Member of Technical Staff (ML Engineer, Recommendations & User Modeling)
USD 220,000-405,000 per year
Used Tools & Technologies
Machine LearningRequired Skills & Competences
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.
Leadership @ 3
Technical Leadership @ 3
Experimentation @ 6
LLM @ 3
- 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.
Details
Perplexity is seeking experienced ML engineers to design, build, and optimize the recommendation systems that power core experiences. The role focuses on reimagining recommendation systems for the LLM era by combining frontier LLMs, personalization from product usage, and continual learning capabilities to recommend actions that help users get the most out of Perplexity.
Responsibilities
- Own the personalization and ranking behind key product surfaces to improve usefulness and drive impact on core user and business metrics.
- Build user modeling that captures intent, preference, and propensity to power more relevant, personalized experiences.
- Design decision layers that balance competing objectives to produce the best overall experience for users.
- Build the data and evaluation foundations that let systems learn and improve with usage.
- Help shape the technical direction of ranking, recommendations, and personalization at Perplexity.
Requirements
- Deep, hands-on experience building production recommendation, ranking, or personalization systems at scale.
- Strong ML fundamentals, including engagement modeling, model calibration, offline and online metrics, and online experimentation.
- Experience integrating LLMs into ranking, retrieval, or personalization pipelines.
- Taste and judgment for how personalization should work in an LLM-native product and curiosity about reimagining it from first principles.
- For technical leadership roles, prior experience setting technical direction for recommendation/ranking projects.
Nice to have
- Experience with large-scale ranking and training infrastructure (multi-stage retrieval and ranking, feature stores, real-time serving).
- Background in user understanding, feed ranking, notifications, growth, or lifecycle modeling.
Our Mission
Perplexity's mission is to power curiosity. The company emphasizes learning, building, integrating, and repeating that cycle to drive change and adoption.
Benefits
- U.S. 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.
- International Benefits: Full-time employees outside the U.S. enjoy a comprehensive benefits program tailored to their region of residence.
Note: USD salary ranges apply only to U.S.-based positions. International salaries are set based on the local market.