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Senior Machine Learning Engineer

Summary

Build and deploy generative AI systems (LLMs, agentic workflows, retrieval) and MLOps pipelines on AWS/Azure for a new AI team in Toronto.

We are building out an AI team in Toronto and are hiring Senior Machine Learning Engineers. This is a build-from-scratch effort on a modern stack, focused on putting AI into production rather than keeping it in the lab. You will work hands-on with LLMs, agentic and multi-agent systems, retrieval-based architectures, and current MLOps practices on a major cloud platform.

This is an early-stage seat on a team that is just forming, so there is real room to influence how things get built and to set technical direction rather than inherit it. They want a hands-on senior engineer who prefers to stay technical rather than move into people management, someone who has shipped ML/AI systems that real users depend on and enjoys working through open-ended problems. You get the independence to make real technical calls, the right resources behind you, strong visibility and a clear path toward Lead or Principal level.

Required Skills & Experience

  • 7+ years building production ML/AI systems
  • Strong hands-on Python and modern ML frameworks (PyTorch)
  • Hands-on generative AI experience: LLMs, retrieval-based architectures, agentic workflows
  • Track record of taking ML systems from prototype to production at scale
  • Production ML engineering: MLOps, containerization (Docker, Kubernetes), cloud (AWS or Azure), workflow orchestration (Airflow), API development (FastAPI)
  • Solid software fundamentals: automated testing, version control, scalable architecture
  • Comfort leading through technical influence and mentorship rather than direct management
  • Bachelor's in CS, Machine Learning, Data Science, Applied Math, or related field

Desired Skills & Experience

  • Master's or PhD
  • Multi-agent or agentic systems built beyond basic LLM integrations
  • Advanced MLOps and cloud-native ML infrastructure at scale
  • Experience with unstructured data
  • Open source contributions, talks, or published work
  • Early-stage or 0-to-1 team experience

What You Will Be Doing

Tech Breakdown

  • 40% Generative AI and Agentic Systems (LLMs, retrieval, multi-agent)
  • 30% Production ML Engineering and MLOps
  • 30% Architecture and System Design

Daily Responsibilities

  • 80% Hands On
  • 20% Team Collaboration

The Offer

  • Bonus eligible

You Will Receive The Following Benefits

  • Medical, Dental, and Vision Insurance
  • Vacation Time

Current Vacancy: Yes

Use of AI in Hiring: No

Applicants must be currently authorized to work in the Canada on a full-time basis now and in the future.

Posted By: Seif Tadros

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