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Flexible Remote Machine Learning Engineer Jobs in Toronto, ON

Vancity

Machine Learning Engineer Lead

Toronto, ON · Remote

This position is remote and open to candidates located in British Columbia or Ontario. While this ... Permanent employees receive flexible benefit packages that can be tailored annually to meet ...

YO AI Labs

Machine Learning Engineer - Remote

Toronto, ON · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

Equinix

Principal Machine Learning Engineer

Toronto, ON · Remote

Job Summary As a Principal Machine Learning Engineer, you will design, build, deploy, and scale machine learning and generative AI systems that power real-world products. You will work closely in AI ...

Serve Robotics

Lead Machine Learning Engineer

Toronto, ON · Remote

CA$225K - CA$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 ...

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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, 68% Full Time, 28% Part Time, and 3% Contract. Highlights an 80% Physical, 1% Hybrid, and 19% Remote job distribution.

Machine Learning Engineer

NTENT

Toronto, ON • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago

Job description

Machine Learning Engineer
Position: Full time
Location: Toronto, Ontario (Initially Remote)
About Us:
NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search technologies directly into their business-to-consumer offerings. We are a unique group of brilliant minds intent on discovering, learning and building. We work in a vibrant atmosphere, with an emphasis on personal and professional development. This is an opportunity to tackle complex problems usually reserved for a handful of large companies in the search industry.
About the Opportunity:
We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven 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 search and ranking, recommendation, personalization, dialog/conversation management).
Keywords:
Machine learning, natural language processing, learning-to-rank, online learning, deep learning, interactive machine learning, machine teaching, conversational agents, human computer interaction
Duties and Responsibilities:
  • Design, implement, and deploy machine learning algorithms.
  • Manage machine learning algorithm lifecycle.
  • Coordinate data collection and annotation efforts.
  • Work with real-time data and content coming from various data sources.
  • Manage machine learning data pipelines.
  • Design tests for machine learning algorithm effectiveness and performance monitoring.
  • Design tools and interfaces for interactive machine learning and teaching.
  • Research and development on cutting-edge machine learning technologies.
Qualifications and Skills:
  • Graduate degree in Computer Science with a strong background in machine learning required.
  • Strong problem-solving abilities, solid background in algorithms and data structures required.
  • Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus.
  • Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required.
  • Experience with distributed and streaming data technologies (eg. Hadoop, Spark, Kafka) required.
  • Experience with building and deploying API's with Docker and Kubernetes required.
  • Experience with natural processing tasks (eg. named entity recognition, language modeling, vector representations) required.
  • Experience with Elastic Search, Lucene a plus but not required.
  • Experience with ranking algorithms a plus but not required.
  • Experience with interactive machine learning (eg. active learning, reinforcement learning, machine teaching) a plus but not required.
The ideal candidate will be self-motivated, possess excellent communication skills (both oral and written) and be able to work independently. A keen interest in various aspects of natural language processing is essential in our multi-disciplinary team.
We offer a full comprehensive benefits package including medical, dental and vision. Employees receive a generous time off (PTO) plan and 13 holidays per year. We also offer 401(k) benefits, long term disability benefits and life.

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