Clera
Founding AI Engineer
About this role
Join a seed-stage construction AI startup as a founding engineer to build computer vision and LLM systems that transform messy blueprints and construction documents into actionable intelligence. You'll own the full ML lifecycle—from data and modeling to production deployment—with significant influence over technical direction and product impact.
What you'll do
- Develop and deploy computer vision, multimodal AI, and LLM models on real-world construction documents in production
- Own end-to-end ML pipelines including data preparation, model training, experimentation, and inference optimization
- Rapidly prototype and iterate on models based on user feedback and production data
- Collaborate with product and users to identify and solve high-impact problems
- Handle practical engineering work including data labeling, ETL, and deployment as part of a small founding team
- Communicate technical tradeoffs and progress clearly across the team
What they're looking for
- Computer vision and multimodal AI
- Large language models (LLMs)
- Production ML systems and deployment
- Data pipelines and ETL
- Python and ML frameworks (TensorFlow, PyTorch, etc.)
- Technical communication and stakeholder management
- Full ML lifecycle ownership
- Problem-solving with messy, heterogeneous data
Benefits
- Early-stage equity as a founding team member
- Significant ownership and influence over technical direction
- High-impact role directly improving housing, hospitals, and schools
- Collaborative team environment with strong communication culture
- Opportunity to shape product and company from the ground up
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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.
View all jobs at CleraLikely interview questions
- Walk us through a computer vision or LLM model you've trained and deployed to production. What were the biggest challenges with real-world data?
- Describe your experience with the full ML lifecycle—how have you gone from raw data to a model serving users or generating business value?