💫 Company | B2B, Deep Tech, AI native

📏 Size | 10 people

🌱 Stage | Seed

🧢 Role | ML Research Engineer

🪜 Level | Mid to Senior

✨ Tech | Python (FastAPI), PyTorch, TensorFlow, HuggingFace

📍 Based | Toronto, Canada

💻 Working | flexible-hybrid / remote-friendly

💰 Offer | $150-200k CAD

Hi 👋

Workonomics are partnering with a deep-tech startup mapping how the global economy connects.

Think - unsupervised learning, a growing dataset that spans millions of real-world signals, and a fresh take on how market relationships are analysed.

They’re using cutting-edge, foundational-level AI (not just simple LLM wrapping) to solve a surprisingly hard problem: how do you reliably track who competes with whom, and how that changes over time?

With backing from top investors, a healthy runway, and Series A on the horizon, they’re now hiring a ML Research Engineer to help:

• design and fine-tune embedding models
• build advanced vector-based data representations
• innovate with unsupervised learning
• develop retrieval systems capable of handling billions of vectors
• solve complex challenges in entity resolution and scale systems globally with MLOps

They're ideally looking for someone with:

• a MSc and/or PhD in ML (or related fields)
• appreciation for data exploration, cleaning, and rapid prototyping
• hands-on experience with vector-based similarity methods
• expertise building LLM systems optimised for speed and scalability
• a passion for open-source (half the current team were found through their contributions)

If this sounds like you, please hit apply for more specifics about the company and role.