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Added 13 mins ago
C1
Senior Data Engineer, Microsoft Fabric - 6 month contract-(Hybrid)
Central 1
Vancouver, BC
- $85 to $100 CAD / hour
- Contract
Central 1 is seeking a highly experienced Senior Data Engineer and Microsoft Fabric Subject Matter Expert (SME) to lead the design, implementation, and optimization of enterprise-scale data…
Added 13 mins ago
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Data Engineer
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- $70 to $80 CAD / hour
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Added 13 mins ago
C1
Senior Data Engineer, Microsoft Fabric - 6 month contract-(Hybrid)
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Added 43 mins ago
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- Full-time
…scalable, and responsible AI solutions. We are seeking a Sr. AI/ML Engineer, RAIB to lead the development, evaluation, governance, and operationalization of machine learning and Generative…
Added 3 hours ago
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Data Engineer, RBC Amplify 2027, Toronto
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McKesson

Sr. AI/ML Engineer, RAIB

Mississauga, ON, Canada

$99,100 - $132,100 · Full-time

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Job details

Pay: $99,100 - $132,100
Job type: Full-time
Apply by: Nov 26, 2026
Experience: ● 7+ years of experience designing, developing, deploying, and supporting production machine learning solutions.
Posting language: English
Posted: Oct 26, 2026

Original job description

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

About the Role

At McKesson, we are advancing healthcare through trusted, scalable, and responsible AI solutions. We are seeking a Sr. AI/ML Engineer, RAIB to lead the development, evaluation, governance, and operationalization of machine learning and Generative AI solutions. This role combines deep technical expertise in ML engineering with a strong focus on Responsible AI practices, model governance, AI risk management, explainability, and production-scale deployment.

You will partner with cross-functional stakeholders to build high-quality AI systems that are secure, reliable, explainable, and aligned with business and regulatory requirements while helping shape McKesson's AI engineering standards.

What You'll Do

Lead the design, development, testing, and deployment of machine learning and Generative AI solutions using Python and modern ML frameworks.

Review, validate, and challenge models developed by internal and external teams to ensure quality, performance, and risk compliance.

Establish model evaluation frameworks for predictive models, LLMs, and GenAI applications.

Conduct fairness, bias, and disparate impact assessments using tools such as Fairlearn and AIF360.

Develop explainability and interpretability capabilities using SHAP, LIME, model cards, and documentation standards.

Lead AI safety and GenAI evaluation activities, including red teaming, hallucination testing, toxicity assessment, and guardrail validation.

Implement model monitoring, drift detection, observability, and AI risk controls within production environments.

Partner with engineering, product, security, and governance teams to drive AI best practices, innovation, and operational excellence.

Basic Requirements

7+ years of experience designing, developing, deploying, and supporting production machine learning solutions.

Bachelor's degree in computer science, Engineering, Data Science, Mathematics, or a related technical field, or equivalent experience.

Experience with Python, as well as CI/CD and CLI/scripting tools

Experience deploying classical machine learning models solving classification, regression, and time series forecasting problems

Experience in managing ML infrastructure at scale in a cloud provider such as Azure (preferred) or AWS programmatically with infrastructure as code

Hands-on experience with machine learning frameworks such as PyTorch and scikit-learn.

Experience building and deploying ML models and data pipelines in production environments.

Knowledge of model evaluation, validation, and performance measurement techniques.

Demonstrated experience collaborating across technical and business teams to deliver complex AI initiatives.

Preferred Skills/Experience

Experience evaluating and governing Large Language Models (LLMs) and Generative AI applications.

Hands-on expertise with Fairlearn, AIF360, SHAP, and LIME.

Experience with AI explainability, transparency, and model documentation practices.

Knowledge of AI safety testing, red teaming, hallucination detection, toxicity monitoring, and guardrail implementation.

Experience with model observability, drift detection, AI monitoring platforms, and MLOps tooling.

Familiarity with Responsible AI frameworks and standards such as NIST AI RMF, ISO 42001, or comparable governance frameworks.

Experience establishing AI risk management controls and audit-ready governance processes.

Proven ability to mentor engineers, drive technical standards, and influence enterprise AI strategy.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$99,100 - $132,100

McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:

McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.

McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

McKesson job postings are posted on our career site: careers.mckesson.com.

McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com or (Canada) Accessibility@mckesson.ca. Resumes or CVs submitted to this email box will not be accepted.

Join us at McKesson!

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More about this job

Responsibilities

Lead the development, evaluation, and operationalization of machine learning and Generative AI solutions while ensuring compliance with responsible AI practices. Collaborate with cross-functional teams to implement model monitoring, risk controls, and AI safety standards across production environments.

Requirements

Requires 7+ years of experience in designing and deploying production machine learning solutions with proficiency in Python and modern ML frameworks. A bachelor's degree in a technical field is required, along with experience in cloud infrastructure and model governance.

Skills

Python
Machine Learning
Generative AI
Model Governance
AI Risk Management
PyTorch
Scikit-learn
Fairlearn
AIF360
SHAP
LIME
CI/CD
Cloud Computing
MLOps
Data Pipelines
Model Monitoring

Benefits

Annual bonus
Long-term incentive opportunities

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Machine Learning
Generative AI
Python
PyTorch
Scikit-learn
Fairlearn
AIF360
SHAP
LIME
CI/CD
Azure
AWS
MLOps
Model Governance
AI Risk Management
Red Teaming
Hallucination Detection
Drift Detection
Infrastructure as Code
Healthcare
Data Science
Predictive Modeling
Explainability
NIST AI RMF
ISO 42001
Observability
Cloud Computing
Software Engineering
Regulatory Compliance

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