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Early Career Research Engineer

Parallel Web Systems · Palo Alto, California

Location
Palo Alto, California, United States
Employment
Full time
Level
Mid level
Posted
7 months ago

About this role

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.

About you

You're a researcher who thinks like an engineer, or an engineer who thinks like a researcher. You've worked on information retrieval systems, embedding models, or neural ranking at scale, or you're deeply curious about the fundamental problems that emerge when training models to understand and serve billions of web documents. You thrive in the space between theory and production, where elegant solutions must also run efficiently on real infrastructure. You're comfortable reading papers from SIGIR and RecSys one day and debugging distributed training pipelines the next.

The role

You'll design and train the models that power Parallel's APIs: the intelligence layer that helps AI agents find exactly what they need from the open web. This means tackling research problems that most labs encounter only at hyperscale: How do you train embedding models that capture semantic intent across diverse query types? How do you balance model expressiveness with sub-second retrieval latency? How do you maintain index freshness when the web updates constantly, without rebuilding from scratch?

Unlike traditional search engines built for human queries, you're building for AI agents that issue complex, multi-hop queries and expect structured, programmatic responses. This is information retrieval reimagined for the LLM era, work that combines classical IR techniques with modern deep learning, applied at a scale that demands new solutions.

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

As published by Parallel Web Systems. Applications are handled on their site.

Skills this posting mentions

Apache SparkArtificial IntelligenceInformation Retrieval

About Parallel Web Systems

At Parallel Web Systems, we’re bringing a new web to life: it’s built with, by, and for AIs. Our work spans innovations across crawling, indexing, ranking, retrieval, and reasoning systems.

All 21 openings at Parallel Web Systems

One click, then it is written

Apply to Parallel Web Systems with a resume written for this role.

Queue Early Career Research Engineer and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Parallel Web Systems’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • 25 sent a week, free
  • No card
  • Nothing sent until you say so

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Put this to work

Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board Parallel Web Systems publishes. Refolk is not the employer and does not handle their hiring. Applications go to Parallel Web Systems directly.