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David AI

Backend Software Engineer

San Francisco$165k–$225kfulltimemidAdded today

About this role

David AI, a Series B-funded audio data research company, is seeking a Backend Engineer to build scalable systems and pipelines that process terabytes of speech data daily. You'll design APIs, deploy ML/DSP solutions, and collaborate with researchers to advance audio AI training data infrastructure.

What you'll do

  • Design and build scalable backend systems and data processing pipelines handling terabytes of audio data
  • Architect and maintain APIs and services used by thousands of users daily
  • Build, deploy, and evaluate LLM and DSP-based solutions for dataset analysis
  • Iterate rapidly on research hypotheses by collaborating with researchers and operations teams
  • Stay current with cutting-edge technologies in backend, data engineering, ML, and signal processing
  • Deploy backend infrastructure supporting new data collection initiatives

What they're looking for

  • Backend engineering (2+ years)
  • Scalable systems and API design
  • Data pipeline architecture
  • Node.js and TypeScript
  • PostgreSQL and AWS
  • Production infrastructure and reliability
  • ML model deployment (bonus)
  • Digital signal processing (bonus)

Benefits

  • Unlimited PTO
  • 100% health, dental, and vision coverage for most plans
  • FSA & HSA access
  • 401k access
  • Daily meals via DoorDash plus office snacks
  • Unlimited company-sponsored Barry's fitness classes
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David AI

David AI builds audio data research platforms that help customers process and understand massive volumes of audio data for AI model training. The company is hiring software engineers across backend, full-stack, security, and product engineering roles to develop scalable infrastructure, distributed systems, and user-facing tools.

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Likely interview questions

  • Describe a data pipeline you built that handled significant scale—what challenges did you face and how did you solve them?
  • How would you approach designing an API that needs to serve thousands of concurrent users processing large audio datasets?
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