Manager, AI Solutions

Heads up: this posting is for future opportunities rather than one specific open role. If you apply, we’ll add you to our candidate network and may reach out when relevant roles come up.

Axial Search is a specialist executive search firm built for one kind of hire: leaders who help organizations navigate AI transformation. Apply today to express your interest in roles like this one.

Visit our website to learn more about our process and explore free tools for your job search, including our live job market dashboard with salary, skills and hiring trend data from thousands of AI transformation roles.

What the market looks like

We've tracked over 3,500+ mid-level postings in AI/ML engineering across Canada in the last six months, with Toronto, Vancouver, and Montreal anchoring the majority of hiring. Technology, financial services, and IT services companies are driving the strongest demand, with salaries typically ranging from $140,000 to $270,000 depending on scope and location. The strongest candidates in this cohort combine hands-on technical depth—shipping ML systems, training models, or building data pipelines—with the ability to mentor junior engineers and translate technical work into business outcomes. Hybrid work is now standard in this segment, particularly in major Canadian tech hubs.

Job responsibilities

• Own the design and delivery of AI/ML solutions end-to-end, from problem scoping through production deployment and monitoring

• Lead a team of 2–5 engineers, providing technical direction, code review, and career development while staying hands-on with architecture and implementation

• Partner with product, data, and engineering stakeholders to define ML requirements, success metrics, and project roadmaps

• Drive best practices around model validation, testing, and governance; establish processes for reproducibility and documentation

• Build and maintain data pipelines, feature stores, and infrastructure supporting training and inference workflows

• Evaluate and integrate third-party ML tools, frameworks, and cloud services (AWS, Azure, GCP) to accelerate delivery

• Communicate technical progress, blockers, and recommendations to non-technical stakeholders; translate business goals into technical scope

Candidate requirements

• 4–7 years of hands-on experience building, training, and deploying machine learning models in production environments

• 2+ years leading or mentoring engineers, with demonstrated ability to grow junior talent and foster collaborative team culture

• Strong foundation in Python, SQL, and at least one ML framework (PyTorch, TensorFlow, scikit-learn); comfort working across the full ML stack

• Experience designing and owning data pipelines, feature engineering, and model evaluation; familiarity with MLOps practices and tools

• Track record translating ambiguous business problems into well-scoped ML projects and delivering measurable impact

• Clear communication skills; ability to explain technical concepts to product, business, and non-technical audiences