Pave-posted 5 days ago
$140,000 - $196,000/Yr
Full-time • Mid Level
San Francisco, CA

At Pave, we're building the industry’s leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision. Top tier companies like OpenAI, McDonald’s, Instacart, Atlassian, Synopsys, Stripe, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 58% of Forbes AI 50 use Pave to benchmark compensation. The future of pay is real-time & predictive, and we’re making it happen right now. We’ve raised $160M in funding from leading investors like Andreessen Horowitz, Index Ventures, Y Combinator, Bessemer Venture Partners, and Craft Ventures.

  • Own critical services like user authentication and authorization.
  • Build foundational data infrastructure and models powering Pave’s compensation intelligence platform.
  • Drive large, complex initiatives across the organization.
  • 2+ years of full-time backend engineering experience building data intensive applications.
  • Familiarity with modern web technologies such as TypeScript and Node.js.
  • Strong computer science fundamentals and familiarity with modern design patterns.
  • Experience with data infrastructure, pipelines/ETLs, and data modeling.
  • Exposure to ML/AI workflows is a plus.
  • Execution-oriented and thrive in fast-paced environments.
  • Growth mindset and eager to learn new technologies and problem domains.
  • Comprehensive Medical, Dental and Vision coverage for you and your family.
  • Flexible PTO and the ability to work from anywhere in the world for a month.
  • Lunch & dinner stipends as well as fully stocked kitchens.
  • Quarterly education stipend for professional development.
  • Robust parental leave to bond with your new family.
  • Commuter stipend to help you collaborate in person.
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