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Clera

Founding AI Engineer

San Francisco$120k–$180kfulltimemidAdded today

About this role

Join a seed-stage AI startup as a founding engineer to build computer vision and multimodal AI systems that streamline construction workflows. You'll own the intelligence layer end-to-end, from modeling and data pipelines to production deployment, working directly with real users on high-impact problems in cost estimation and permit processing.

What you'll do

  • Design and deploy production computer vision and multimodal AI models on noisy construction documents (blueprints, permits, PDFs)
  • Own end-to-end intelligence systems including data pipelines, model training, and inference infrastructure
  • Rapidly prototype and iterate models based on user feedback and production data
  • Handle full-stack AI tasks including data labeling, ETL, and pragmatic deployment work
  • Collaborate with product and end users to identify and solve high-impact problems
  • Communicate technical tradeoffs and progress transparently across the small founding team

What they're looking for

  • Computer vision (model training and deployment in production)
  • Machine learning systems and production AI infrastructure
  • Multimodal AI and LLM techniques
  • Data pipelines and ETL
  • Python or similar ML-focused languages
  • Rapid prototyping and iteration
  • Document processing (PDFs, images, text)
  • Strong communication and collaboration

Benefits

  • Early-stage equity as a founding team member
  • High autonomy and direct ownership over impactful AI systems
  • Seed-stage environment with 0-to-1 building opportunity
  • Direct collaboration with end users in construction industry
  • Full-time, in-office role in San Francisco
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Walk us through a computer vision or ML project you deployed to production—what were the biggest challenges with real-world data?
  • Describe your experience building end-to-end AI systems. What parts of the pipeline did you own versus hand off?
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