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Ai Math Jobs in Toronto, ON (NOW HIRING)

University degree in computer science, engineering, data science, mathematics, or a related discipline. * 5+ years of professional experience in machine learning, data science, AI engineering, or a ...

The AI Architect is responsible for designing and developing scalable AI solutions aligned to a ... D. in a quantitative field such as computer science, applied mathematics, statistics or machine ...

Bachelors degree in Computer Science, Mathematics, Statistics, or a related field * Experience building AI agents or LLM-based applications in production environments * Experience with machine ...

About the job - AI Engineer Join the Engineering Team, where you'll help shape and build our ... You hold a Bachelor's degree (or higher) in Computer Science, Statistics, Mathematics, or ...

About the job - AI Engineer Join the Engineering Team, where you'll help shape and build our ... You hold a Bachelor's degree (or higher) in Computer Science, Statistics, Mathematics, or ...

Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent Other Qualification * Stay up to date with advancements in AI, LLMs, RAG, autonomous agents ...

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Ai Math information

Will AI take mathematicians jobs?

AI mathematicians use artificial intelligence tools to assist with complex calculations, data analysis, and problem-solving. While AI can automate routine tasks, mathematicians' roles involving creativity, interpretation, and theoretical development remain essential and are unlikely to be fully replaced by AI.

Which 3 jobs will survive AI?

AI Math professionals, data scientists, and software engineers are likely to continue thriving as their roles involve complex problem-solving, creativity, and oversight of AI systems. These jobs require advanced analytical skills, domain expertise, and adaptability to evolving technologies, making them less susceptible to automation.

What is the difference between Ai Math vs Data Analyst?

AspectAi MathData Analyst
Required CredentialsMathematics, Computer Science, AI certificationsStatistics, Data Analysis, Business Intelligence certifications
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness settings, consulting firms, corporate departments
Industry UsageAI development, machine learning projects, researchData interpretation, reporting, decision support

Ai Math professionals focus on developing algorithms and models using advanced mathematics and AI techniques, often working in research or tech environments. Data Analysts interpret data to provide insights and support business decisions. While both roles require analytical skills, Ai Math emphasizes algorithm creation and AI research, whereas Data Analysts focus on data visualization and reporting.

What is an AI Math specialist?

An AI Math specialist is a professional who applies advanced mathematical concepts and techniques to develop, analyze, and improve artificial intelligence algorithms and models. Their work often involves linear algebra, calculus, probability, statistics, and optimization methods to design effective machine learning and deep learning systems. AI Math specialists collaborate with data scientists, engineers, and researchers to solve complex problems, ensure model accuracy, and enhance the performance of AI-driven solutions.

How does an AI Math specialist typically collaborate with data scientists and software engineers within a project team?

AI Math specialists play a crucial role in multidisciplinary teams by developing mathematical models and algorithms that underpin AI solutions. They frequently work alongside data scientists to refine statistical methods, validate results, and optimize data processing techniques. Collaboration with software engineers is also common, as AI Math specialists help translate theoretical models into efficient, scalable code for production environments. This teamwork ensures that AI systems are both mathematically sound and technically robust, fostering innovation and effective problem-solving.

What are the key skills and qualifications needed to thrive as an AI Math Specialist, and why are they important?

To thrive as an AI Math Specialist, you need strong mathematical foundations in linear algebra, calculus, probability, and statistics, typically supported by a degree in mathematics, computer science, or a related field. Proficiency with programming languages like Python, experience with machine learning frameworks (such as TensorFlow or PyTorch), and familiarity with data analysis tools are essential. Critical thinking, problem-solving, and effective collaboration are important soft skills for tackling complex challenges and working in interdisciplinary teams. These skills enable the development, implementation, and optimization of robust AI models and solutions.

What is the highest paid math job?

The highest paid math-related job is often a quantitative analyst or financial mathematician, earning six-figure salaries or higher, especially in finance and investment banking. These roles typically require advanced degrees, strong programming skills, and expertise in statistical modeling and risk assessment.

Can I work in AI with a math degree?

Yes, a math degree provides a strong foundation for AI roles such as AI researcher, data scientist, or machine learning engineer. These positions often require knowledge of algorithms, statistics, programming languages like Python, and familiarity with AI frameworks such as TensorFlow or PyTorch.
What job categories do people searching Ai Math jobs in Toronto, ON look for? The top searched job categories for Ai Math jobs in Toronto, ON are:
What cities near Toronto, ON are hiring for Ai Math jobs? Cities near Toronto, ON with the most Ai Math job openings:
Infographic showing various Ai Math job openings in Toronto, ON as of June 2026, with employment types broken down into 72% Full Time, 22% Part Time, and 6% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

CA$103K - CA$192K/yr

Full-time

Medical, Life, Retirement

Posted 16 days ago


Job description

Application Deadline:

06/29/2026

Address:

100 King Street West

Job Family Group:

Data Analytics & Reporting

The Senior Applied AI Engineer is responsible for designing, developing, and deploying advanced Gen AI and machine learning solutions that
drive business value in Wealth Management. This role blends deep technical expertise with financial domain knowledge, collaborating with
cross-functional teams to deliver scalable, secure, and compliant AI products. The engineer will design and implement GenAI and agent-based
systems to enhance advisor workflows, client engagement, and operational efficiency.
Key Responsibilities

  • Contribute to the overall Wealth Management AI strategy formulation and execution
  • Architect and build GenAI-powered applications for Wealth management use cases.
  • Liaise with relevant technology teams to build and deploy Gen AI solutions
  • Lead the solution development, from ideation to prototyping and liaise with our partners to facilitate production and monitoring.
  • Collaborate with product managers, data scientists, engineers, and business stakeholders to translate requirements into technical solutions.
  • Integrate AI solutions with existing platforms (CRM, portfolio management, data warehouses) and ensure interoperability.
  • In collaboration with the risk and RAIOps teams, ensure all AI solutions meet performance, security, and regulatory standards.
  • Leverage best practices in MLOps, model governance, and responsible AI.
  • Stay current with industry trends, emerging AI technologies in financial services AI.
  • Document technical designs, create demos, and support enablement and adoption across the organization.

Required Skills and Tools

  • Advanced proficiency in Python and machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
  • Experience building Copilot Studio Agents.
  • Proficiency with GenAI, LLMs (e.g., OpenAI, Google Gemini, Anthropic), and agent orchestration frameworks (LangChain,
    LangGraph, AutoGen).
  • Strong understanding of cloud platforms (Azure, AWS, GCP) and MLOps tools (MLflow, Kubeflow, Airflow).
  • Familiarity with financial services workflows, data privacy, and compliance requirements.
  • Strong hands-on experience with both AWS and Azure cloud environments, including their AI/ML, data, and deployment
  • toolsets (e.g., SageMaker, S3, Lambda, Azure Functions, Azure ML, Blob Storage)
  • Proficiency with Kubernetes for container orchestration and deployment of scalable AI solutions.
  • Experience with Docker, and CI/CD pipelines
  • Expertise in data engineering, model deployment, and monitoring.
  • Knowledge of API integration, microservices, and scalable system architecture.
  • Excellent problem-solving, communication, and stakeholder management skills.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
  • 10+ years of experience in AI/ML engineering, with at least 2 years in financial services or regulated industries or a combination of relevant experience and education.
  • Proven track record of designing and deploying production-grade AI solutions.
  • Experience working in Agile teams and collaborating with cross-functional stakeholders.
  • Demonstrated ability to mentor and lead technical teams.

Advanced level of proficiency:

  • Gen AI, Mathematics
  • Critical thinking.
  • Creative reasoning.
  • Computational Thinking and Programming.
  • Deep Learning.
  • Machine Learning.
  • Scaling Models.
  • Continuous Integration and Continuous Delivery/Deployment.
  • ML algorithm.
  • Verbal & written communication skills.
  • Analytical and problem solving skills.
  • Influence skills.
  • Collaboration & team skills; with a focus on cross-group collaboration.
  • Able to manage ambiguity.

Salary:

$103,200.00 - $192,000.00

Pay Type:

Salaried

The above represents BMO Financial Group's pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit:https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other's differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.