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Clera is seeking an on-site AI/ML engineer in San Francisco to build the intelligence layer for blueprint understanding. You will focus on computer vision and production ML, applying the latest techniques to real construction documents and iterating rapidly with direct user feedback.
The role requires hands-on CV/ML experience, strong Python skills, and a track record of shipping AI systems to production in an early-stage startup.
Join an early-stage, seed-funded AI startup in the construction tech space that is automating the process of reading construction blueprints and extracting material and cost data. The company is tackling a massive, largely manual industry problem using cutting-edge computer vision and AI — and this hire will be a core part of the technical foundation. If you love hard problems, shipping quickly, and iterating directly with users, this is the role for you.
Focus on the intelligence layer — ML models, algorithms, and AI systems — rather than the application layer
Apply the latest computer vision, LLM, and AI techniques to real construction documents (blueprints, plans, specs)
Ship initial prototypes fast, then iterate based on direct user feedback
Help design and coordinate a model-garden architecture for blueprint understanding
Work on object detection models and supporting ML pipelines in production
Required:
Hands‑on applied Computer Vision and ML/Deep Learning experience
Strong Python skills
Proven 0‑to‑1 builder — you have shipped AI/ML systems to production
Growth mindset: we value trajectory over pedigree
Comfortable with ambiguity, early‑stage grind, and getting deep into hard problems
Communicates with empathy and honesty
Nice to Have:
Prior founder or startup experience — you've built something people used or paid for
Background in construction, architecture, or related trades
Impact‑driven mindset aligned with making housing and infrastructure more accessible
Salary: $100,000 – $180,000 USD annually
Employment: Full-time
Visa sponsorship: Not available
This role is fully on‑site in San Francisco, CA. Candidates must be SF‑based or willing to relocate.