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Machine Learning Engineer, Ranking Pipeline

Parallel • United States
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AI Summary

Own the multi-stage ranking pipeline that narrows web-scale candidates to the best passages for a query. Push precision and recall across retrieval, first-pass ranking, and neural reranking while balancing quality, latency, and cost. Requires a relevant bachelor's degree or equivalent and experience aligned with internal job level requirements.

Key Highlights
Owns the multi-stage ranking pipeline from web-scale candidates to best passages
Balances precision, recall, latency, and cost across retrieval and reranking
Grades outcomes on real usage rather than offline proxies
Fully in-person between Palo Alto HQ and San Francisco office
Compensation range is $150K - $300K

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Key Responsibilities
Own the multi-stage ranking pipeline that narrows a web-scale set of candidates down to the handful of best passages for a query
Push precision and recall across fast candidate retrieval, lightweight first-pass ranking, and heavier neural reranking
Decide how much compute each query deserves
Grade everything on real usage outcomes rather than offline proxies

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Benefits & Perks
Competitive salary
Generous equity
Visa sponsorships
401K plans
Daily lunch & office snacks
Dinner at the office
Unlimited vacation
Caltrain pass reimbursement

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Job Description

About Us

Parallel is a web infrastructure company. Our products are used by leading businesses in sales, marketing, insurance, and coding to build best-in-class AI agents with flexible and powerful programmatic access to the web.

We've raised $230 million from Kleiner Perkins, Sequoia, Index Ventures, Spark Capital, Khosla Ventures, First Round, and Terrain to build the web for AIs. We're currently valued at $2 billion and we're forming a world-class team of engineers, designers, marketers, sellers, researchers, and operational experts to achieve our mission.

The role:

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Job Overview
Posted Nov 04, 2026
Employment Full-time
Experience Not Applicable
Location United States
Category Machine Learning
Company Parallel
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