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Artificial Intelligence Machine Learning Engineer Jobs in Toronto, ON

The gap isn't in intelligence; it's in execution. Thri5 continually scans data across the business ... Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

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Artificial Intelligence Machine Learning Engineer information

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON?

For Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Toronto, ON with the most Artificial Intelligence Machine Learning Engineer job openings:

Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Toronto, ON as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 76% Full Time, 20% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Senior Machine Learning Engineer, GFT

Toronto, ON

Royal Bank of Canada
Banking and Credit Intermediation • 10K+ employees

Full-time

Posted 13 days ago


Key responsibilities

  • Develop, and productionize advanced GenAI and AI solutions to address complex business challenges

  • Optimize and deploy ML models and AI agents using modern frameworks and best practices

  • Build and maintain production-grade ML infrastructure including data pipelines, model serving endpoints, and monitoring systems


Job description

Job Description

What is the opportunity?

Come and be part of our innovative and high-performing GenAI and Mobile team if you are a talented, tenacious, meticulous, and results-focused individual who thrives on building production-grade GenAI applications. We are seeking an experienced Senior Machine Learning Engineer to help shape, develop, and deliver AI applications and proof-of-concepts (POCs) across diverse business lines. The successful candidate will collaborate with stakeholders to identify opportunities, develop impactful solutions, and drive the adoption of advanced AI technologies across the organization.

Are you a talented, creative, and results-driven professional who thrives on delivering high-performing GenAI applications at scale? Come join us!

Global Functions Technologies impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformational IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.

As a Senior Machine Learning Engineer, you will be a key member of a team, developing and deploying large-scale GenAI applications for enterprise use cases. You will build and optimize LLM-based solutions, RAG systems, agentic workflows, and production ML infrastructure that powers effective decision-making across RBC. You will be working in a cross-functional team that supports various businesses and you will have an opportunity to work with different kinds of datasets, modern AI frameworks, and cloud-native platforms. You will collaborate with other developers, ML engineers, and business partners to deliver medium to high-complexity GenAI initiatives with measurable business impact.

What will you do?

  • Develop, and productionize advanced GenAI and AI solutions, ensuring they address complex business challenges with measurable impact and deliver tangible ROI
  • Optimize and deploy state-of-the-art ML models and AI agents, leveraging modern frameworks (e.g., LangChain, LangGraph, or similar) and best practices for scalability, reliability, and maintainability
  • Contribute to experimentation and continuous improvement cycles, including robust prompt engineering, model evaluation, A/B testing, and performance optimization of production GenAI systems
  • Build and maintain production-grade ML infrastructure including data pipelines, model serving endpoints, monitoring systems, and automated deployment workflows
  • Implement RAG (Retrieval-Augmented Generation) systems using vector databases, semantic search, and knowledge retrieval techniques to enhance LLM capabilities
  • Develop agentic AI workflows with multi-step reasoning, tool use, and orchestration to solve complex business problems autonomously
  • Collaborate with product managers, data engineers, and business stakeholders to translate requirements into technical specifications and working solutions
  • Write clean, maintainable, well-documented code following software engineering best practices including code reviews, testing, and version control
  • Stay current with emerging GenAI technologies and research, evaluating new models, frameworks, and techniques for potential adoption
  • Participate in technical design discussions and contribute to architectural decisions for GenAI applications and ML infrastructure
  • Ensure responsible AI practices including bias detection, model explainability, security, privacy, and compliance with enterprise governance standards
  • Document technical solutions, architectures, and processes to enable knowledge sharing and team scalability

What do you need to succeed?

Required Qualifications

  • 5+ years of experience in machine learning engineering with 2+ years focused on production ML systems
  • Hands-on experience building GenAI applications using LLMs, RAG, agents, or similar technologies in production environments
  • Strong proficiency in Python and modern ML frameworks (LangChain, LangGraph, Hugging Face, OpenAI API, Anthropic Claude, etc.)
  • Solid understanding of LLM architectures, prompt engineering, fine-tuning, and optimization techniques
  • Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes)
  • Practical knowledge of MLOps practices including CI/CD, model monitoring, versioning, and deployment automation
  • Experience with vector databases (Pinecone, Weaviate, pgvector, Chroma) and semantic search systems
  • Strong problem-solving skills with ability to break down complex problems into implementable solutions
  • Excellent collaboration and communication skills with ability to work effectively in cross-functional teams
  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)

Preferred Qualifications

  • Experience in financial services or highly regulated industries with understanding of compliance and data privacy requirements
  • Knowledge of agentic AI architectures and multi-agent orchestration frameworks
  • Experience with real-time streaming data and event-driven architectures
  • Familiarity with distributed systems and high-scale data processing
  • Experience with A/B testing frameworks and experimentation platforms
  • Contributions to open-source ML/AI projects or technical blog posts
  • Experience with graph databases and knowledge graph construction
  • Understanding of transformer architectures and attention mechanisms

What's in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

  • Leaders who support your development through coaching and managing opportunities
  • Ability to make a difference and lasting impact on enterprise AI adoption across RBC
  • Work in a dynamic, collaborative, progressive, and high-performing team
  • Opportunities to do challenging work and build cutting-edge GenAI solutions at scale
  • Access to emerging technologies and continuous learning in the rapidly evolving AI landscape
  • Exposure to diverse business problems across Risk, Finance, Compliance, and other critical functions
  • Competitive compensation and benefits package

#LI-post

#TECHPJ

Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages

Additional Job Details

Address:

RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-08-28

Application Deadline:

2026-10-02

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Employment Type: FULL_TIME