Location: Hybrid (Toronto, New York or San Francisco preferred) 2-3 days in office

Type: Full-time Permanent

Canadian Salary: $180-230k CAD + 10% bonus + Pre IPO equity

A high-growth, VC-backed SaaS company is hiring AI/ML Engineers to help scale real-world ML features for an industry-transforming platform used daily by thousands. This isn't academic research - it's high-impact AI deployed into production.

You'll join a tight-knit team of senior engineers working at the intersection of ML, software engineering, and infrastructure. If you've built LLM-powered systems and enjoy shipping features that customers actually use - this is the one to look at.

What You'll Do

• Build and deploy production ML models (LLMs, NLP, embeddings) using Python + PyTorch on AWS SageMaker
• Integrate cloud-based LLM APIs (ChatGPT, Bedrock, etc.) into large-scale applications
• Develop full-stack features (Node.js + React) that deliver ML to the user interface
• Implement MLOps best practices: CI/CD, ML monitoring (e.g., Wandb, MLFlow), vector DB integration
• Collaborate with product managers and engineers to deliver ML features end-to-end
• Own your code: write tests, review PRs, contribute to team best practices

What We're Looking For

• 5+ years software engineering experience (Python + JavaScript/Node)
• 2+ years hands-on ML experience (ideally with LLMs, NLP, vector search, etc.)
• Familiarity with MLOps, production deployment, AWS cloud (SageMaker a big plus)
• Experience building APIs (REST/GraphQL) and integrating ML into full-stack apps
• A startup mindset - scrappy, driven, and excited to solve real customer problems
• Bonus: Degree in CS/Engineering from a top-tier university (Stanford, MIT, Berkeley, CMU, Waterloo, etc.)

Why This Role?

• Strong compensation
• Meaningful equity in a fast-growing, pre-IPO SaaS company
• Join a well-funded unicorn scaling aggressively across North America
• Small, high-performing team with tons of technical ownership and velocity
• Real-world impact - you're not prototyping, you're shipping production ML
• Own critical ML systems powering a product used daily by thousands