Senior Machine Learning Engineer

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

The role involves building generative AI and agentic systems from scratch, focusing on moving ML models from prototype to production. Responsibilities include system architecture, MLOps implementation, and providing technical mentorship to the team.

Requires over 7 years of experience building production ML systems with strong proficiency in Python and PyTorch. A Bachelor's degree in a quantitative field is required, with a Master's or PhD preferred.

• Medical Insurance • Dental Insurance • Vision Insurance • Vacation Time

• Microsoft AzurePreferred
• KubernetesPreferred
• Automated testingPreferred
• DockerPreferred
• Amazon Web ServicesPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Python
• PyTorch
• Large Language Models
• Retrieval-Based Architectures
• Agentic Workflows
• MLOps
• Docker
• Kubernetes
• AWS
• Azure
• Airflow
• FastAPI
• System Design
• Automated Testing
• Version Control
• Scalable Architecture

• Software
• Technology
• Engineering
• Data & Analytics
• Science & Research

Minimum education

Bachelor’s degree

Minimum experience

5+ years

Apply by

Sep 4, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level