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Added 27 days ago
Python developer
I8IS - Infiniti Software Solutions
Mississauga, ON
Full-time
Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and…
Added 27 days ago
GenAI Developer/Engineer - Toronto
Caspian One
Toronto, ON
Contract
We’re looking for Senior Gen AI Developer/Engineers to join a growing AI team, building real-world generative AI solutions within a large-scale financial services environment. You’ll work…
Added 23 days ago
Lead Applied AI and Data Scientist | IFS Copperleaf
IFS
Vancouver, BC
Full-time
Both halves sit on the AI Foundation. Today that foundation includes a GenAI agent framework, a tool system, vector stores, streaming and telemetry, and a separate ML service; the near-term…
Added 13 days ago
Senior Machine Learning Engineer, GFT
RBC
Toronto, ON
Full-time
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…
Added 27 days ago
Data Engineer
FDM Group
Montreal, QC
Full-time
Automatiser via Python (contrôles opérationnels, tests unitaires/BDD)
Added 25 days ago
Principal Data and Applied Scientist
SAP
Montreal, QC
Hands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.
Added 18 days ago
Senior Director, Data & AI, Wealth Management Canada
Royal Bank of Canada
Toronto, ON
Full-time
…high impact program in Canada. You will leverage best in class GenAI, AI, and ML capabilities to deliver new insights and capabilities with global reach. You will also be responsible for…
Added 19 days ago
Senior Full Stack Developer, Research Technology
Royal Bank of Canada
Toronto, ON
Full-time
…Capital Markets overall. We are seeking a senior full-stack developer who will be responsible for the development, enhancement and deployment of digital research applications which power…
Added 24 days ago
Software Development Engineer in Test, Creativity Apps (SDET)
Apple
Vancouver, BC
The Video Apps team is looking for a Software Developer in Test with a background in video/photo editing to contribute to the development of innovative tools for creative professionals,…
Added 25 days ago
Senior Director, Data & AI, Wealth Management Canada
RBC
Toronto, ON
Full-time
…high impact program in Canada. You will leverage best in class GenAI, AI, and ML capabilities to deliver new insights and capabilities with global reach. You will also be responsible for…
Added 24 days ago
GenAI Architect
Lantern
Calgary, AB · Edmonton, AB · Vancouver, BC · Toronto, ON
Proficiency in Python and experience with cloud-native development.
Added 25 days ago
Senior Full Stack Developer, Research Technology
RBC
Toronto, ON
Full-time
…Capital Markets overall. We are seeking a senior full-stack developer who will be responsible for the development, enhancement and deployment of digital research applications which power…
Added 25 days ago
Principal Data and Applied Scientist
SAP
Montreal, QC
Hands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.
Added 25 days ago
Backend AI Engineer
Nexxa.AI
Remote, Canada
Full-time · Remote
Design, build, and maintain backend services and APIs that power GenAI, LLM, and Computer Vision model integrations across Nexxa's products.
Added 25 days ago
Lead Full-Stack GenAI Engineer
Vancity
Vancouver, BC
Full-time
As a Lead Full-Stack GenAI Engineer, you will lead the hands-on delivery of secure Generative AI and agentic AI solutions from discovery and prototype through production deployment,…
Added 1 month ago
Software Architect - AI Accelerated Engineering Lead
Slalom
Calgary, AB
Full-time
Manage GenAI-driven teams: Orchestrate multi-developer environments where AI agents and engineers work side by side - ensuring productivity, quality, and responsible adoption.
Added 1 month ago
Manager, ML/AI Engineer, Data & AI
KPMG
Calgary, AB · Vancouver, BC · ON · Toronto, Ontario
Full-time
…recommendation, anomaly detection) using tech stack such as Python and common ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch, Azure ML Studio, Databricks…
Added 1 month ago
Senior Consultant, ML/AI Engineer, Data & AI
KPMG
Calgary, AB · Vancouver, BC · ON · Toronto, Ontario
Full-time
…recommendation, anomaly detection) using tech stack such as Python and common ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch, Azure ML Studio, Databricks…
Added 20 days ago
BCG Platinion | Senior AI Tech Consultant, Tech Advisory & Delivery
Boston Consulting Group
Toronto, ON
$160,000 CAD / year
Full-time
Added 26 days ago
Data Scientist Manager
Sanofi
Toronto, ON
Full-time
AI & GenAI driven transformation of market access and payer strategies
Added 26 days ago
Lead Data Scientist
Sanofi
Toronto, ON
Full-time
AI & GenAI driven transformation of market access and payer strategies
Added 26 days ago
AI Engineer
Sanofi
Toronto, ON
Full-time
AI & GenAI driven transformation of market access and payer strategies
Added 1 month ago
AI/ML Data Engineer - Wealth Management and Financial Services
J&M Group
Toronto, ON
Contract
Advanced Python development for data pipelines, AI/ML solutions, automation, and API integrations.
Added 22 days ago
AI-First Quality Engineering Lead
Royal Bank of Canada
Toronto, ON
Full-time
You will partner across technology, product, and platform teams to lead a full shift-left transformation powered by GenAI, intelligent automation, and agentic engineering practices. This is…
Added 27 days ago
AI-First Quality Engineering Lead
RBC
Toronto, ON
Full-time
You will partner across technology, product, and platform teams to lead a full shift-left transformation powered by GenAI, intelligent automation, and agentic engineering practices. This is…

KPMG

Manager, ML/AI Engineer, Data & AI

UNAVAILABLE, Calgary, AB, Canada
UNAVAILABLE, Vancouver, BC, Canada
ON, Canada
UNAVAILABLE, Toronto, ON, M5H 2S5, Canada

Job type: Full-time
Apply by: Jul 28, 2027
Experience: 5+ years of professional experience in machine learning, data science, AI engineering, or a related field, with demonstrated experience delivering production ML solutions.
Posting language: English
Posted: Jul 28, 2026

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Original job description

Overview

At 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.

Are you a technically strong and business‑oriented Machine Learning / AI Engineer with a passion for building and scaling intelligent solutions? Our team is looking for a hands‑on engineer with deep experience in AI/ML engineering and AI/ML engineering operations who can partner with clients to design, build, and operationalize AI‑powered solutions at scale.

This role will focus on translating advanced analytics, machine learning, and generative AI use cases into secure, scalable, and production‑ready solutions across on-prem and cloud environments (ideally on Azure but also GCP and AWS).

What you will do

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 (e.g., forecasting, classification, recommendation, anomaly detection) using tech stack such as Python and common ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch, Azure ML Studio, Databricks MLFlow).
Develop and optimize AI and GenAI solutions using state-of-the-art tools and platform (AI Foundry, GCP Vertex AI, AWS Sagemaker and Bedrock).
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.

What you bring to the role

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 (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.

Certifications (Preferred)

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).

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $103,000 to $135,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.

KPMG BC Region Pay Range Information

The expected base salary range for this position is $101,000 to $130,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.

Providing you with the support you need to be at your best

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

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.

AI Usage

We embrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.

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.

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More about this job

Responsibilities

The role involves partnering with clients to design, build, and operationalize scalable AI and machine learning solutions. You will be responsible for developing end-to-end ML pipelines, implementing MLOps best practices, and collaborating with cross-functional teams to solve complex business problems.

Requirements

Candidates must have a university degree in a relevant field and at least 5 years of professional experience in machine learning or AI engineering. Proficiency in Python, cloud platforms, and experience with generative AI and MLOps are essential for this position.

Skills

Python
Machine Learning
Artificial Intelligence
Generative AI
MLOps
Azure
Google Cloud Platform
AWS
Data Engineering
Model Deployment
CI/CD
Large Language Models
Prompt Engineering
Retrieval-Augmented Generation
Consulting
Stakeholder Management

Benefits

Comprehensive and competitive Total Rewards program
Bonus awards

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Artificial Intelligence
Generative AI
Python
Azure ML Studio
Databricks
MLFlow
TensorFlow
PyTorch
Scikit-learn
Vertex AI
AWS Sagemaker
Bedrock
MLOps
CI/CD
LLMs
RAG
Cloud Computing
Data Engineering
Model Governance
Explainability
Bias Detection
Spark
Consulting
Strategy
Production-ready
Distributed Processing
Feature Engineering
Statistics
Data Analysis

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