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Flexible Remote Machine Learning Engineer Jobs in Toronto, ON

Moneris

Senior Manager, Data Engineering

Toronto, ON · On-site +1

CA$142K - CA$177K/yr

Enable DataOps and MLOps practices, including feature engineering pipelines and machine learning ... Comprehensive Total Rewards Program, including performance-based bonuses, flexible benefits ...

YO AI Labs

Mental Health Expert - Remote

Toronto, ON · Remote

$200 - $350/hr

AI/ML Engineer Job Type: Full-Time Location: Remote Job Summary We are seeking an experienced AI/ML ... machine learning applications. Key Responsibilities * Design, implement, and optimize AI/ML ...

Bits In Glass

Intern

Toronto, ON · On-site +1

Remote/Hybrid Description As a ML Developer Intern you will work closely with the ML Developers and ... Engineering or related * Prior experience in development of machine learning solutions, including ...

DataVisor

Delivery Engineer - Canada

Toronto, ON · Remote

CA$80K - CA$120K/yr

Its patented unsupervised machine learning technology, advanced device intelligence, powerful ... Position Overview: We are seeking a Delivery Engineer to join our Delivery team. The ideal ...

Waabi

Research Engineer, Neural Rendering

Toronto, ON · On-site +1

CA$134K - CA$235K/yr

You are familiar with the internals of modern machine learning (diffusion models, vision ... Flexible hours and Work from Home support. * Daily drinks, snacks and catered meals (when in office)

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All JobsMachine Learning Engineer JobsFlexible Remote Machine Learning Engineer JobsFlexible Remote Machine Learning Engineer Jobs in Toronto, ON

Flexible Remote Machine Learning Engineer information

What is a flexible remote machine learning engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

What are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.

How does a flexible remote work arrangement impact collaboration and project delivery for machine learning engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

What is the difference between Flexible Remote Machine Learning Engineer vs Data Scientist?

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in Toronto, ON?

For Flexible Remote Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Flexible Remote Machine Learning Engineer jobs in Toronto, ON look for?

The top searched job categories for Flexible Remote Machine Learning Engineer jobs in Toronto, ON are:

Flexible Remote Machine Learning Engineer jobs near you
Infographic showing various Flexible Remote Machine Learning Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, and 3% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution.

Lead Data Scientist- IBM Watson

Fusemachines

Toronto, ON • Remote

Contractor

Re-posted 28 days ago

Job description

About Fusemachines

Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail,  manufacturing, and government.
Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
Type: Full-time, Remote

About the Role

A Lead Data Scientist is responsible for designing and implementing data-driven solutions to complex business problems. The role requires extensive experience in data analysis, agentic AI, statistical modeling, machine learning, and data visualization, as well as the ability to lead a team of data scientists and collaborate with cross-functional teams.

Responsibilities
  • Team Leadership: Lead a team of data scientists to develop innovative solutions to complex business problems. Mentor and develop the skills of junior data scientists and provide feedback and guidance to help them improve their work.
  • Collaboration: Collaborate with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers to develop and implement data-driven solutions.
  • Strategic Assessment: Assess the business needs of clients and identify areas where AI can be used to improve processes, reduce costs, or increase revenue.
  • Solution Design: Design and implement statistical models, machine learning algorithms, predictive analytics models, and agentic systems to solve business problems.
  • Communication: Communicate technical insights and recommendations to non-technical stakeholders in a clear and concise manner.
  • Continuous Learning: Stay up-to-date with the latest developments in data science, machine learning, and artificial intelligence, and apply new technologies and techniques to solve business problems.
  • Pipeline Management: Responsible for developing, implementing, and managing end-to-end machine learning pipelines. This will involve building, deploying, and maintaining machine learning models, as well as ensuring data quality and system stability.
 Requirements for the Role
  • Education: Bachelor's, Master's, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field.
  • Experience: 6+ years of total experience in Data Science, Machine Learning & Generative AI.
  • Cloud Computing: 4+ years of hands-on experience with AWS, including deep expertise in deploying models and managing compute environments.
  • IBM WatsonX: 2+ years of hands-on experience with IBM WatsonX
  • Agentic AI Tools: Experience with LangGraph, Google ADK or similar.
  • Agentic Architectures : Experience with advanced RAG & multi-agent systems.
  • Programming: Strong programming skills in languages such as Python, R, C++, and SQL.
  • Frameworks: Hands-on experience with ML frameworks, such as PyTorch or TensorFlow.
  • Leadership: Experience leading data science teams and managing multiple projects simultaneously.
Soft Skills: Strong problem-solving skills, attention to detail, and excellent communication skills (both written and verbal).
Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

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