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Clera

Founding AI Engineer

San Francisco$120k–$180kfulltimemidAdded 6 days ago

About this role

Join this early-stage construction tech startup as a founding AI engineer to build computer vision and LLM systems that extract actionable insights from blueprints and construction documents. You'll own the end-to-end AI pipeline—from modeling through deployment—enabling faster material takeoffs and cost estimation for housing, hospitals, and schools.

What you'll do

  • Apply computer vision, LLM, and multimodal AI techniques to process construction documents and blueprints
  • Build and maintain data pipelines and inference systems that handle noisy, heterogeneous inputs at scale
  • Rapidly prototype models and iterate based on production data and user feedback
  • Own the intelligence layer end-to-end, including model development, data labeling, ETL, and deployment
  • Collaborate with product and users to identify and solve high-impact problems
  • Communicate technical progress, tradeoffs, and decisions clearly across the founding team

What they're looking for

  • Computer vision (document analysis, OCR, image processing)
  • Large language models and prompt engineering
  • Multimodal AI and model integration
  • ML production systems and MLOps
  • Data pipeline engineering and ETL
  • Python and ML frameworks (PyTorch, TensorFlow, or similar)
  • Rapid prototyping and iteration
  • Clear technical communication

Benefits

  • Equity in early-stage startup
  • Base salary $120,000–$180,000 annually
  • On-site team environment in San Francisco
  • Impact on housing and infrastructure affordability
  • Founding team autonomy and direct influence on product direction
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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 production AI system you built or shipped—what were the biggest challenges with real-world data?
  • Describe your experience applying computer vision or LLMs to unstructured or messy data. How did you handle quality issues?
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