Member of Technical Staff (Model Behavior Architect)
USD 200,000-300,000 per year
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
Communication @ 6
LLM
Python @ 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
We're looking for a Model Behavior Architect to help build Perplexity's AI products and evaluations. You'll sit within our AI team and collaborate closely with research and product teams, designing prompt and context engineering strategies to deliver high quality user experiences across multiple domains and models.
This role is equal parts craft and science. You'll develop a deep understanding of our answer engine by pressure-testing model capabilities and working across our AI infrastructure (including system and tool prompts, skills, and evaluations) to create a stellar product experience for our users.
You'll serve as a go-to expert on prompting, model quality, and behavioral consistency across new product features and model releases.
Responsibilities
- Context Engineering: Design, test, and optimize context strategies and system prompts that shape answer engine behavior across products, features, and use cases.
- Evaluation Systems: Build automated and semi-automated evaluation pipelines that measure model quality, catch regressions, and scale across product surfaces.
- Model Launch Support: Partner with research and engineering to validate model behavior before and during rollouts, ensuring smooth transitions with no degradation.
- Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects—for both internal and production-facing systems.
- Cross-functional Collaboration: Work closely with design, product, and research teams to translate product goals into concrete model behavior requirements.
- Knowledge Sharing: Help engineers across teams build intuition for prompt design, context engineering, and evaluation best practices.
- Staying Current: Track the latest alignment, evaluation, and prompting techniques from industry and academia, and bring the best ideas back to the team.
Requirements
- Experience designing evaluations, benchmarks, or metrics for AI systems.
- Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.
- Ability to manage multiple concurrent projects in a fast-moving environment.
- Strong experience with Perplexity or other frontier AI models in production settings.
- Demonstrated experience with Python—you'll prototype, debug, automate, and build systems at scale.
- 3+ years of experience working with LLMs in a product or research setting.
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.
- 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.
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