Safety Engineer
Exa
Safety Engineer
Exa
AI-driven search API for real-time data
Exa is an applied AI lab building a search engine unlike the world has ever seen. We build massive-scale infra to crawl the entire web, train state-of-the-art embedding models to process it, and design super high performant vector databases to retrieve over it. We now power search for Cursor, Cognition, HubSpot, and over 400,000 developers and have raised $350m from Lightspeed, Benchmark, and a16z.
Our ultimate goal is to build perfect search over all the world's information, far beyond Google. If you want to build massive-scale ML systems that will define the way the new AI world consumes information, this is the place for you.
As a Safety Engineer - Abuse and Fraud, you will be thinking about Exa’s platform security, abuse of Exa as a platform, and safety in content. You will ensure that users are abiding by the terms of service and look at content moderation of text and multimodal.
Build fraud detection systems
Be responsible for overall moderation
Create our strategy within Exa, making sure our systems are compliant
Interact with other stakeholders in different parts of the org, and content construction
Experience in fraud and moderation systems
Experience in content moderation
Any kind of experience in a large web property
Exa is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, marital status, pregnancy or related conditions, criminal histories consistent with applicable law, or any other basis protected by applicable law.
Exa.ai builds an AI-driven search API that returns high-quality, real-time data from the web for use in AI training and applications. The API lets developers fetch the best data with just a few lines of code, and customers access it via a subscription plan that includes 1000 free searches per month with additional paid plans. This approach differs from traditional search by focusing on data quality and relevance for AI needs rather than keyword-based results, enabling scalable data delivery for models and apps. The company aims to grow its search product and establish itself as the data layer for AI applications, backed by its Series A funding from Lightspeed Venture Partners, Nvidia, and Y Combinator.
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