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About the Role

We are seeking a technically strong and business-oriented Machine Learning / AI Engineer with a passion for building and scaling intelligent solutions. This role involves partnering with clients to design, build, and operationalize AI-powered solutions at scale, translating advanced analytics, machine learning, and generative AI use cases into secure, scalable, and production-ready solutions across on-prem and cloud environments.

Responsibilities

Partner with clients to understand business problems and identify opportunities to apply AI and advanced analytics solutions.
Translate business and analytical requirements into end-to-end ML/AI solution design.
Execute ML/AI engineering tasks including exploratory data analysis, data preparation, model development using tech stack such as Python and common ML frameworks.
Develop and optimize AI and GenAI solutions using state-of-the-art tools and platforms.
Operationalize AI/ML pipelines using AI/ML Ops best practices, including model deployment versioning, CI/CD, automated testing, and monitoring.
Implement model monitoring, performance tuning, drift detection, and retraining strategies in production environments.
Collaborate with data engineers to ensure reliable, scalable data pipelines that support model training and inference.
Apply responsible AI principles, including explainability, bias detection, model governance, and compliance with security and privacy standards.
Support client workshops, technical discussions, and stakeholder presentations related to AI strategy, solution design, and implementation.

Requirements

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 related field, with demonstrated experience delivering production ML solutions.
Strong proficiency in Python for data analysis, machine learning, and model development.
Hands-on experience with machine learning frameworks/libraries and platform tools.
Solid understanding of ML algorithms, statistics, model evaluation techniques, and feature engineering.
Experience designing and implementing end-to-end ML pipelines, including data preprocessing, model training, validation, deployment, and monitoring.
Practical experience with ML Ops practices, including CI/CD, model versioning, experiment tracking, and automated retraining.
Experience deploying ML models to cloud environments (Azure, AWS, or GCP) with an understanding of cloud-native architecture and security principles.
Familiarity with big data or distributed processing frameworks (e.g., Spark) is an asset.
Experience with generative AI, large language models (LLMs), prompt engineering, or retrieval-augmented generation (RAG) is essential.
Experience with fine-tuning foundational models is an asset.
Strong consulting and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Proven ability to collaborate within cross-functional and multi-disciplinary teams to solve complex business problems.

Skills

Python
scikit-learn
TensorFlow
PyTorch
Azure ML Studio
Databricks MLFlow
AI Foundry
GCP Vertex AI
AWS Sagemaker
AWS Bedrock
ML Ops
CI/CD
Model Versioning
Automated Testing
Monitoring
Drift Detection
Retraining Strategies
Spark
Generative AI
Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Foundational Models
Cloud-native architecture
Security principles
Explainability
Bias Detection
Model Governance
Security Standards
Privacy Standards

Location

Ontario
BC

Work Type

Full-time

Experience Level

5+ years of professional experience

Education Level

University degree in computer science, engineering, data science, mathematics, or a related discipline.
Cloud AI / ML certifications (e.g., Azure AI Engineer Associate or better, AWS Machine Learning Specialty or better, Google Professional ML Engineer or better, Databricks ML Engineer Associate or better, Databricks Generative AI Engineer).

Salary/Compensations

Ontario Region: $103,000 to $135,000
BC Region: $101,000 to $130,000

Benefits

May be eligible for bonus awards.
Comprehensive and competitive Total Rewards program.

About the Company

KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges.
Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage.
Join a firm where your career can make a difference.
Our Values, The KPMG Way: Integrity, we do what is right | Excellence, we never stop learning and improving | Courage, we think and act boldly | Together, we respect each other and draw strength from our differences | For Better, we do what matters
We embrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes.
We believe technology should empower human judgment, not replace it.
It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.

Equal Opportunity

KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential.
A diverse workforce is key to our success and we believe in bringing your whole self to work.
We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.
Adjustments and accommodations throughout the recruitment process: At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel.
We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best.
Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements.
You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process.
If you require support, please contact KPMG’s Employee Relations Service team by calling 1-888-466-4778.