Founding Machine Learning Engineer

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AI Startup · Toronto, Canada (In-Person downtown Toronto)

About Us
We're solving one of the largest problems in the physical world: housing that's too slow and too expensive to build. The $2 trillion construction industry runs on human expertise that doesn't scale - so we're building the AI that understands what to build and how to build it.
We start with the costliest problems for general contractors - the multi-million-dollar decisions that Claude cannot solve. Tyce Agent wins more projects and estimates costs on multi-million-dollar builds live at one of the landmark construction companies today.
We just closed a 7-figure round and are hiring to build the best AI platform for construction.

What You'll Do
You'll own the AI core of the product - how we ingest, understand, retrieve, and reason over customers' documents. This is the heart of our moat, and it's where the hardest, most interesting problems live.
• Building a Context/Knowledge Graph around our customers knowledge bases - process messy PDFs, Excels into AI-native context representation
• Improve on our agent harness - agentic search and any unique tools as part of our platform
• Build the evaluation harness that keeps quality high as we ship fast.
• Ship latest AI featureas day-to-day alongside the founders and shape the AI roadmap.
We're on a modern, lean stack: FastAPI, PostgreSQL, Pydantic-AI, Logfire, AWS, with a React Router / TypeScript frontend.

Required Qualifications
• Mid-to-senior level of AI/engineering experience.
• Strong in Python; comfortable shipping production systems, not just notebooks.
• Hands-on experience building and evaluating LLM/RAG or ML systems.
• Go-getter mindset, personal agency, fast learner, excellent verbal and writing skills.
• Full-time, in-person in downtown Toronto

Nice-to-have Qualifications
Having any of these is a strong plus — tell us your superpower:
• Built and evaluated an AI agent / RAG system for real-world performance.
• Document parsing / OCR / information-extraction experience (PDF, DOCX, tables, layout).
• Retrieval/search background (embeddings, ranking, vector + keyword hybrid).
• Comfortable full-stack enough to ship your own features end-to-end.
• Competitive programmer (e.g. ACM ICPC).

Check us out at https://www.tyce.ai/