EngineeringOn-site

Member of Technical Staff (Software Engineer, Applied AI)

Perplexity · On-site

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Last seen by MeritLog September 12, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Perplexity's Ashby job board and last checked it on September 12, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: On-site
Salary: $220K - $405K
Location: San Francisco

Hiring context

How this role compares at Perplexity

Perplexity has 115 live roles in MeritLog’s catalog across 11 job families, and 41 of them are in engineering. 99 of those listings publish a pay range, a disclosure rate of 86%.

This role's posted range of $220K - $405K sits above 69% of the 98 other Perplexity roles quoted over the same currency and period.

Perplexity concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

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.

What they're asking for

5+ years experience building and shipping robust AI products for large-scale, user-facing or data-driven products.ExperiencePreferred
Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large scale parallel developments.SkillPreferred
In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement.SkillPreferred
Proven collaborator and communicator; excels in high-velocity, cross-functional teams.SkillPreferred
Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI.SkillPreferred
BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience).EducationPreferred
Experience with LLM context engineering or harness engineering.SkillPreferred
Experience in mid-training or post-training frontier open source modelsSkillPreferred
Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc).SkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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).

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