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Early Career Research Engineer

Parallel Web Systems — Tracked from its ashby job board

Palo Alto New Grad $150K – $300K • Offers Equity Posted Jan 24, 2026
AI/LLMML

About the 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

What the index says about this role

  • First seen by JobLarper — Aug 2, 2026, 6 days ago. Older postings collect hundreds of applicants — a tailored résumé matters more the longer a role has been live.
  • What Machine Learning Engineer roles ask for — across 1,108 indexed openings: ML (78%), AI/LLM (55%), Python (53%), REST/APIs (38%), Cloud (25%). This posting names ML, AI/LLM.
  • Parallel Web Systems is hiring actively — 10 open roles indexed.

Derived from the 27,000 roles JobLarper indexes daily from official company boards — not from the job description above.

⚡ JobLarper watched this role appear on Parallel Web Systems's official board on Jan 24, 2026. Sign up free to get alerted minutes after roles like this go live, and tailor your real résumé to the exact description — nothing invented.

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