Parallel Systems
Member of Technical Staff, Search Ranking
San Francisco or Palo Alto · Staff+
Sponsorship not specifiedDetected 28 days ago
SparkAgentic AIFirewallResearch
About the role
- You: Have deep intuition for relevance, feature engineering, and the trade-offs between quality, latency, and cost.
- Think rigorously about how ranking, retrieval, and agent behavior inform one another, and how to train models that serve all three.
- You care about your research being applied to product and systems that millions use.
Responsibilities
- You will own the multi-stage ranking pipeline that narrows a web-scale set of candidates down to the handful of best passages for a query, spending the least compute necessary to do it well.
Compensation
- Competitive salary
- Visa sponsorships
- Daily lunch & office snacks
- Dinner at the office
Benefits
- Generous equity
- Unlimited vacation
- Caltrain pass reimbursement
Company info
- 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.
- Job: You will own the multi-stage ranking pipeline that narrows a web-scale set of candidates down to the handful of best passages for a query, spending the least compute necessary to do it well. You will push precision and recall across fast candidate retrieval, lightweight first-pass ranking, and heavier neural reranking, decide how much compute each query deserves, and grade everything on real usage outcomes rather than offline proxies.
- You: Have deep intuition for relevance, feature engineering, and the trade-offs between quality, latency, and cost. Think rigorously about how ranking, retrieval, and agent behavior inform one another, and how to train models that serve all three. You care about your research being applied to product and systems that millions use.
- 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.
- Job: You will own the multi-stage ranking pipeline that narrows a web-scale set of candidates down to the handful of best passages for a query, spending the least compute necessary to do it well.
- You will push precision and recall across fast candidate retrieval, lightweight first-pass ranking, and heavier neural reranking, decide how much compute each query deserves, and grade everything on real usage outcomes rather than offline proxies.
- It's on us to ensure real-world outcomes for our customers.
Visa & Work Authorization
- Visa sponsorships
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This listing is sourced directly from Parallel Systems's careers page and normalized into a canonical job model.