Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Toronto, ON, United States
Posted
14 hours ago
DockerFastAPIAWSMLOpsMachine LearningAirflowAzureGenerative AIKubernetesLLMPyTorchPython
Job Description
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
Tech Breakdown
The Offer
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.
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
- 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
Tech Breakdown
- 40% Generative AI and Agentic Systems (LLMs, retrieval, multi-agent)
- 30% Production ML Engineering and MLOps
- 30% Architecture and System Design
- 80% Hands On
- 20% Team Collaboration
The Offer
- Bonus eligible
- 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.
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