At Parallel Web Systems, we are 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. Our first product is a set of APIs for AIs to do more with web data.

We are a fully in-person team based in both San Francisco and Palo Alto, CA. Our organization is flat; our team is small and talent dense.

We want to talk to you if you are someone who can bring us closer to living our aspirational 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.

Job: Research engineer. You will enhance our core research product to train and scale models that serve a web-scale index. This includes shaping model architecture and training strategy, and working closely with systems and product to push research into production.

You: Have deep intuition for modern models and training. You like arguing how search, recommendations, and transformer-based systems converge. You care about research that ships and runs in production at real scale. You have a strong academic foundation, demonstrated through excellence in a demanding program.

Our founder is Parag Agrawal. Previously, he was the CEO and CTO at Twitter. Our investors include First Round Capital, Index Ventures, Khosla Ventures, and many others.