Member of Technical Staff, Search Ranking
At a glance
Senior Software Engineering role at Parallel Web Systems. San Francisco · full-time · $150,000–$300,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Own the ranking flow that reduces web-scale candidates to the strongest passages for each query while limiting compute
- Improve precision and recall through fast retrieval, an initial lightweight ranker and a more intensive neural reranker
- Choose compute levels per query and assess quality using outcomes from real usage rather than offline proxies
- Train models that connect ranking, retrieval and agent behavior
What you bring
- A bachelor’s degree or equivalent preparation through education, training and professional work
- Relevant expertise shown through coursework, training or professional experience
- Strong judgment on relevance, feature design, and balancing quality against latency and cost
Who this fits
This senior role suits someone who can bring research into a product and its supporting systems. You’ll work fully in person at the San Francisco office or the Palo Alto headquarters. Visa sponsorships are offered.
From the employer
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:
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.
About 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.
You might be a good fit if you have:
Bachelor's degree or equivalent combination of education, training, and professional experience
A field relevant to the role as demonstrated through coursework, training, or professional experience
Years of experience required will correlated with the internal job level requirements for this position.
Life at Parallel
Our team works fully in-person, between our Palo Alto HQ and San Francisco office. We’re a flat, talent-dense organization dedicated to solving technical and creative problems.
We seek like-minded individuals who share our passion for applying science, creativity, and consistency to big and complex problems with equally big outcomes. These are our values:
Own customer impact: It’s on us to ensure real-world outcomes for our customers.
Obsess over craft: Perfect every detail because quality compounds.
Accelerate change: Ship fast, adapt faster, and move frontier ideas into production.
Create win-wins: Creatively turn trade-offs into upside.
Make high-conviction bets: Try and fail. But succeed an unfair amount.
Compensation & benefits
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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