Member of Technical Staff (ML Engineer, Recommendations & User Modeling)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Staff Plus From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff (ML Engineer, Recommendations & User Modeling) San Francisco, California, United States, Palo Alto Perplexity is seeking experienced ML engineers to design, build, and optimize the recommendation systems that power core experiences on Perplexity. Perplexity builds AI for those who expect more. Our products are designed to help people find answers, make their most consequential decisions, and complete increasingly ambitious work. Across these use cases, the Perplexity experience must feel deeply personal. Great recommendations and user understanding are central to delighting and delivering for each user. To do this, we are reimagining recommendation systems for the LLM era. Our goal is to combine the intelligence of frontier LLMs, the personalization context that comes from real product usage, and the continual learning capabilities of modern recommendation systems. We build systems that draw on past context and connected data sources to deeply understand each user's needs and recommend the actions that help them get the most out of Perplexity. Why Perplexity is Different - Craftsmanship . We build high quality, tasteful products targeting both AI native and AI curious users. - Ownership . You identify the problem, design the solution and ship it. - Entrepreneurship . We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship . Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership . We amplify each others' strengths, break down silos, and give selflessly to help our

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