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Full Time Senior Machine Learning Engineer Jobs in Toronto, ON

Serve Robotics

Lead Machine Learning Engineer

Toronto, ON · Remote

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

Thri5 Inc.

AI / Machine Learning Engineer

Toronto, ON · On-site

Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that powers our System of Actions. You'll design and implement multi-agent Co-pilot systems that orchestrate ...

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Full Time Senior Machine Learning Engineer information

What is the difference between Full Time Senior Machine Learning Engineer vs Data Scientist?

AspectFull Time Senior Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds models, creates reports for business insights
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, healthcare, research

Full Time Senior Machine Learning Engineers focus on designing, building, and deploying scalable ML models, often working closely with engineering teams. Data Scientists analyze data, develop models for insights, and support decision-making. While both roles require strong analytical skills and knowledge of ML, engineers emphasize deployment and system integration, whereas data scientists focus on data analysis and modeling for insights.

What is a full time senior machine learning engineer?

Full Time Senior Machine Learning Engineers are experienced professionals who design, develop, and deploy advanced machine learning models and systems. They often lead teams, set technical direction, and collaborate with data scientists, engineers, and stakeholders to solve complex problems using data-driven approaches. Their responsibilities include selecting appropriate algorithms, optimizing model performance, and ensuring that machine learning solutions are scalable and maintainable in production environments. Senior engineers typically have several years of experience and a strong background in programming, statistics, and machine learning theory.

What are the key skills and qualifications needed to thrive as a full time senior machine learning engineer, and why are they important?

To thrive as a Full Time Senior Machine Learning Engineer, you need expertise in machine learning algorithms, statistical analysis, programming (commonly Python or R), and a relevant degree such as computer science or engineering. Experience with tools like TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP), and often advanced certifications in ML or data science are highly valued. Strong problem-solving, leadership, and communication skills set top candidates apart by enabling them to lead projects and collaborate effectively across teams. These skills are crucial for designing scalable ML solutions, mentoring peers, and delivering impactful business outcomes.

What types of projects and cross-functional collaboration can a full time senior machine learning engineer expect in their role?

As a Full Time Senior Machine Learning Engineer, you’ll typically work on complex projects that involve designing, deploying, and optimizing machine learning models for real-world applications. You can expect to collaborate closely with data scientists, software engineers, product managers, and domain experts to define project requirements, integrate models into production systems, and iterate based on feedback. This collaborative environment not only fosters innovation but also provides opportunities to mentor junior engineers and contribute to strategic decisions, making the role both technically challenging and highly impactful within the organization.
What are popular job titles related to Full Time Senior Machine Learning Engineer jobs in Toronto, ON? For Full Time Senior Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Full Time Senior Machine Learning Engineer jobs in Toronto, ON look for? The top searched job categories for Full Time Senior Machine Learning Engineer jobs in Toronto, ON are:
Full Time Senior Machine Learning Engineer jobs near you
Infographic showing various Full Time Senior Machine Learning Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Sr. Machine Learning Ops Engineer

McKesson

Mississauga, ON • On-site

CA$99K - CA$132K/yr

Full-time

Re-posted 22 days ago

McKesson rating

7.9

Company rating: 7.9 out of 10

Based on 209 frontline employees who took The Breakroom Quiz

47th of 86 rated pharmaceutical

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.

Job Title

Senior MLOps Engineer

This position follows our Flex & Connect model of 2x per week onsite in Mississauga, ON.

Summary

Join McKesson's growing AI/ML team and play a critical role in operationalizing machine learning and Generative AI solutions at scale. This role focuses on deploying, standardizing, and maintaining production-ready ML and agentic AI systems-enabling consistent, reliable, and optimized delivery of data science innovations that support McKesson's AIM28 strategic initiatives.

What You'll Do
  • Lead deployment and operationalization of ML models and GenAI/agentic solutions, ensuring scalability, reliability, and performance
  • Partner with Data Scientists to identify and automate high-impact model use cases, building end-to-end pipelines (CI/CD, monitoring, alerting)
  • Define and enforce standardized deployment patterns and runbooks across teams
  • Own KTLO (keep-the-lights-on) operations for ML and GenAI systems including health monitoring, logging, and performance tracking
  • Design and implement pipelines for batch, real-time, and event-driven inference
  • Establish observability frameworks (monitoring, logging, lineage, alerting)
  • Enable deployment of agentic AI solutions using tools such as LangChain, LangGraph, Semantic Kernel, and Databricks tools
  • Ensure secure deployment of applications with proper access controls (e.g., Okta integration)
  • Drive cost and performance optimization across ML and GenAI workloads
  • Partner with architecture, compliance, governance, and legal teams to meet enterprise standards
  • Conduct ongoing research into emerging tools and technologies to improve deployment practices
  • Guide and influence architectural decisions while maintaining clear separation between platform and deployment ownership
What You Bring
  • Strong experience deploying ML models into production environments
  • Hands-on expertise with CI/CD pipelines, monitoring, and production ML systems
  • Experience with GenAI or agentic AI frameworks (LangChain, Semantic Kernel, etc.)
  • Knowledge of model observability, drift detection, and operational support
  • Experience working in scaling or early-stage ML environments
  • Proficiency with cloud platforms (AWS, Azure, or GCP)
  • Strong cross-functional collaboration skills (Data Science, Product, Architecture)
  • Ability to drive standardization, automation, and platform maturity
  • Focus on reliability, scalability, and optimization
Minimum Requirements
  • Degree or equivalent and typically requires 7+ years of relevant experience.
Preferable Skills & Experience
  • Experience with Databricks ecosystem (e.g., Databricks Genie)
  • Familiarity with LangChain, LangGraph, or Microsoft Semantic Kernel
  • Exposure to GenAI cost optimization / FinOps practices
  • Experience implementing secure enterprise applications (e.g., Okta)
  • Experience in healthcare or regulated environments
  • Experience scaling ML/AI capabilities from experimentation to production maturity

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, pleaseclick 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.

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