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Product Manager Machine Learning Jobs in Ontario

Manager, Machine Learning Engineering

Toronto, ON · Remote

CA$181K - CA$272K/yr

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing ... Collaborate cross-functionally with MLOps engineering, product management, operations, and data ...

... products. The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web ...

MLOps Experience: 3+ years of hands-on experience in DevOps and MLOps, with a focus on deploying and managing machine learning models in production environments * Infrastructure as Code (IaC)

As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows.

As a Machine Learning Engineer, you will design, build, and operate the platforms, pipelines, and ... and production. * Credential and Secrets Management: Implement secure credential handling using ...

AI/ML Product Manager As an AI/ML Product Manager at Vanguard, you'll help shape how artificial intelligence (AI) and machine learning (ML) enable better outcomes for our clients and our crew. In ...

New

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

Summary: We are currently seeking a Machine Learning Engineer to join our rapidly growing ... Collaborate cross-functionally with engineering, product management, operations and data science to ...

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Every day, we strive to make every interaction, product, and experience remarkably human and ... You'll have regular career, development, and performance conversations with your manager, as well ...

Machine Learning Engineer

Toronto, ON · On-site

CA$82K - CA$154K/yr

Runs machine learning tests and experiments. Trains and retrain systems to prevent drift and ... Take measured risks while protecting the bank by applying our Risk Management Framework in the ...

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Product Manager Machine Learning information

What does a product manager machine learning do?

A Product Manager for Machine Learning oversees the development and deployment of machine learning products or features. They work closely with data scientists, engineers, and business stakeholders to identify opportunities where machine learning can deliver value, define product requirements, and guide projects from conception to launch. Their responsibilities include setting the product vision, prioritizing features, ensuring alignment with business goals, and evaluating the impact of machine learning solutions. They also help bridge the gap between technical teams and non-technical stakeholders by translating complex concepts into actionable plans.

What are the key skills and qualifications needed to thrive as a product manager machine learning?

To thrive as a Product Manager, Machine Learning, you need a solid understanding of product lifecycle management, data analytics, and machine learning concepts—often supported by a technical degree and relevant experience. Familiarity with tools like Python, SQL, JIRA, and machine learning frameworks, as well as certifications such as PMP or Agile, is highly beneficial. Outstanding communication, stakeholder management, and problem-solving skills help you bridge the gap between technical teams and business objectives. These abilities are crucial to successfully guide ML products from ideation to launch, ensuring they deliver real value and align with organizational goals.

How does a product manager machine learning typically collaborate with data scientists and engineering teams?

Product Managers in Machine Learning work closely with both data scientists and engineering teams to translate business objectives into viable AI-driven products. They facilitate communication by defining clear requirements, prioritizing features, and ensuring that the technical roadmap aligns with user needs and company strategy. Regular meetings, progress reviews, and shared documentation are common practices to keep everyone aligned. This cross-functional collaboration is essential for addressing feasibility, optimizing models, and delivering successful products on schedule.

What is the difference between Product Manager Machine Learning vs Data Scientist?

AspectProduct Manager Machine LearningData Scientist
Primary FocusOverseeing ML product development, strategy, and deploymentAnalyzing data, building models, and deriving insights
Required SkillsProduct management, ML understanding, cross-functional collaborationStatistics, programming, data analysis
Work EnvironmentProduct teams, engineering, business stakeholdersData analysis teams, research, engineering
Common CertificationsProduct management certifications, ML coursesData science certifications, programming skills

While both roles involve machine learning, Product Manager Machine Learning focuses on guiding ML products from conception to deployment, working closely with engineering and business teams. Data Scientists primarily analyze data and develop models to extract insights. The roles complement each other but differ in their core responsibilities and skill sets.

What are popular job titles related to Product Manager Machine Learning jobs in Ontario?

For Product Manager Machine Learning jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Product Manager Machine Learning jobs in Ontario look for?

The top searched job categories for Product Manager Machine Learning jobs in Ontario are:

Infographic showing various Product Manager Machine Learning job openings in Ontario as of August 2026, with employment types broken down into 80% Full Time, 19% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

Manager, Machine Learning Engineering

Clio

Toronto, ON • Remote

CA$181K - CA$272K/yr

Full-time

Medical, Dental, Vision

Re-posted 3 days ago


Job description

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of every size to work smarter, faster, and more securely.

We are transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice.

Summary:

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing engineering organization. This role is for someone who is passionate about building innovative solutions and being exposed to new challenges and technologies while making an impact. This role is available to candidates across Canada and the US.

What your team does:

We at Clio have an amazing team that is on a mission to transform the legal experience for all, and our engineering team's goal is to deliver an incredible experience to our customers. In the AI team at Clio, we use the latest in GenAI, and LLMs in particular, along with agentic systems, to build solutions that make our customers' work more streamlined and efficient, giving them more time to focus on their clients' needs. That means going beyond single-shot model calls: we design agentic workflows where models reason over context, use tools, and take multi-step actions on behalf of legal professionals, all grounded in a customer's real data.

A day in the life might look like:
  • Lead a team of ML engineers to bring state of the art AI to Clio's clients, spanning traditional ML models, GenAI, and agentic AI.

  • Guide the team in designing and shipping agentic systems, including retrieval, tool use, orchestration, and the evaluation frameworks that keep them reliable and safe in production.

  • Collaborate cross-functionally with MLOps engineering, product management, operations, and data science to identify new tooling for ML and LLM-driven features for Clio customers.

  • Work in an agile environment with our team of ML engineers, ML ops, and full stack developers across a variety of projects

  • Learn new things, challenge yourself, and hone your craft as an ML and infrastructure expert in a space that is moving fast

  • Participate in diverse projects and collaborate with multiple engineering teams across three countries.

  • Review and provide feedback on code, both from within your own team or across all of Clio.

  • Collaborate with teams across Clio to diagnose, understand, and solve problems, and to build solutions that may span many areas.

  • Teach and learn from those around you, providing constructive feedback and taking on feedback to help grow.

What you may have:
  • Experience in managing high performing teams.

  • Experience with technical evaluations of various ML and LLM products, vendors, out-of-the-box solutions, and conducting quick proof of concepts if necessary.

  • In-depth understanding of LLMs, GenAI, and the competitive landscape, including where the technology is heading.

  • Hands-on familiarity with building agentic systems, such as tool-calling agents, RAG pipelines, prompt and context design, and evaluating agent behavior at scale.

  • Experience in fine-tuning foundational models and/or training language models in-house.

  • Experience to manipulate, clean, and pre-process complex unstructured data for model development.

  • The ability to become fluent in new technologies quickly and work effectively in an ever-evolving environment that includes distributed teams and customers.

  • Demonstrated success in mentorship in software development, particularly using an Agile process and with large scale SaaS products.

  • A diverse base of knowledge that allows you to help your team solve complex technical problems.

  • A history of past projects (including notable successes and lessons learned).

  • Clear and concise communication skills and the ability to build high-trust relationships with fellow Clions and customers.

#LI-Remote

This role is a backfill for an existing position.

What you will find here:

Compensation is one of the main components of Clio's Total Rewards Program. We have developed a series of programs and processes to ensure we are creating fair and competitive pay practices that form the foundation of our human and high-performing culture.

Some highlights of our Total Rewards program include:

  • Competitive, equitable salary with top-tier health benefits, dental, and vision insurance

  • Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin, London, New York City and Sydney) to be in office min. twice per week.

  • Flexible time off policy, with an encouraged 20 days off per year.

  • $2000 annual counseling benefit

  • RRSP matching and RESP contribution

  • Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

The expected salary range for this role is $181,360 to $272,040 CAD. Initial placement within the range is informed by geographic region, experience, and skillset, with room to progress as impact and tenure grow. Final offer amounts will vary based on candidate profile.

Diversity, Inclusion, Belonging and Equity (DIBE) & Accessibility

Our team shows up as their authentic selves, and are united by our mission. We are dedicated todiversity, equity and inclusion. We pride ourselves in building and fostering an environment where our teams feel included, valued, and enabled to do the best work of their careers, wherever they choose to log in from. We believe that different perspectives, skills, backgrounds, and experiences result in higher-performing teams and better innovation. We are committed to equal employment and we encourage candidates from all backgrounds to apply.

Clio provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.

Learn more about our culture atclio.com/careers

We're a Human and High Performing AI company, meaning we use artificial intelligence to improve all of our operations. In recruitment, AI helps us streamline the process for greater efficiency. However, we've built our systems to ensure that a human always reviews AI-generated output, and we never make automated hiring decisions.

Disclaimer: We only communicate with candidates through official @clio.com email addresses.