Clera
Founding Engineer (Applied AI)
About this role
Early-stage construction tech startup seeks a founding engineer to build the AI intelligence layer for automating blueprint analysis and cost estimation. You'll own computer vision and ML systems from research to production, working on a small team to make housing development faster and more affordable.
What you'll do
- Own and advance the AI intelligence layer, focusing on computer vision and ML rather than application development
- Apply state-of-the-art computer vision models and LLMs to solve construction-domain problems
- Build and ship working prototypes quickly while incorporating direct user feedback
- Orchestrate multiple ML models into cohesive AI systems
- Deploy and iterate on AI systems in production environments
- Contribute to early-stage operational work as needed by the team
What they're looking for
- Computer vision and machine learning
- Python
- Deep learning frameworks and techniques
- ML model deployment and production systems
- Large language models (LLMs)
- System design and orchestration
- CS fundamentals or equivalent practical engineering experience
- Rapid prototyping and iteration
Benefits
- Equity as part of founding-team compensation
- On-site role in San Francisco with relocation support
- High-impact work on early-stage product development
- Opportunity to work directly with end users and shape product direction
- Collaborative small team environment
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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 ML system you've taken from zero to production. What were the biggest challenges?
- How do you approach scoping and prioritizing which AI models to build or integrate when time and resources are limited?