Early Career Research Engineer

About us

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.

• 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.

Compensation & benefits

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