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About the Role

KPMG in Canada is seeking a technically strong and business-oriented Machine Learning / AI Engineer passionate about building and scaling intelligent solutions. This role involves partnering with clients to design, build, and operationalize AI-powered solutions at scale, focusing on 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, and model development using 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.
3+ 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 (e.g., scikit-learn, TensorFlow, PyTorch, Azure ML Studio, Databricks MLFlow).
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/ML Ops
CI/CD
Model Versioning
Experiment Tracking
Automated Retraining
Cloud Environments (Azure, AWS, GCP)
Cloud-Native Architecture
Security Principles
Spark
Generative AI
Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Fine-tuning Foundational Models
Consulting Skills
Communication Skills

Location

Ontario Region
BC Region

Work Type

Full-time

Experience Level

3+ 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

$77,000 to $102,000 (Ontario Region)
$73,000 to $100,000 (BC Region)

Benefits

Eligible for bonus awards
Comprehensive and competitive Total Rewards program

About the Company

KPMG in Canada's people bring unique perspectives to Canada’s most important challenges.
KPMG's Values: Integrity, Excellence, Courage, Together, For Better.
KPMG is 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 are available.
AI Usage: AI tools may help with organizing applications or surfacing relevant qualifications, but no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals.