Senior Consultant, ML/AI Engineer, Data & AI

KPMG

$73K — $100K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • University degree in computer science, engineering, data science, mathematics, or related discipline.
  • 3+ years of experience in machine learning, data science, or AI engineering with production ML solutions.
  • Proficiency in Python for machine learning and data analysis.
  • Experience with ML frameworks/tools such as scikit-learn, TensorFlow, PyTorch, and Azure ML Studio.
  • Understanding of ML algorithms, statistics, and model evaluation techniques.
  • Hands-on experience with ML Ops practices, including CI/CD and automated retraining.
  • Experience deploying ML solutions to cloud environments (Azure, AWS, GCP) with a focus on security principles.

Responsibilities

  • Partner with clients to identify AI opportunities and business challenges.
  • Translate business needs into ML/AI solution designs.
  • Execute ML engineering tasks such as data preparation and model development.
  • Develop AI and GenAI solutions using advanced tools and platforms.
  • Operationalize ML pipelines following industry best practices.
  • Implement model monitoring and retraining strategies in production.
  • Collaborate with data engineers to ensure robust data pipelines.

Benefits

  • Comprehensive and competitive Total Rewards program.
  • Supportive work environment focused on integrity and excellence.
  • Opportunities for continued learning and professional growth.
  • Collaborative culture encouraging diversity and respect for individual strengths.
  • Engagement in advanced technology initiatives that empower human judgment.
Full Job Description
Overview

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.
  • 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.

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 $77,000 to $102,000 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 $73,000 to $100,000 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

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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