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Machine Learning Engineer Opt Jobs in Toronto, ON

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 ...

As a Machine Learning Engineer, you will design, build, and operate the platforms, pipelines, and reusable patterns that take models from experimentation to production at scale. You will work with ...

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

We are currently seeking a Machine Learning Engineer to join our rapidly growing engineering team. This role is for someone who is passionate about building innovative solutions and being exposed to ...

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence. Our Company Invision AI is building a ...

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence. Our Company Invision AI is building a ...

Machine Learning Engineer

Toronto, ON · Remote

CA$110K - CA$130K/yr

Your Role Clarius Mobile Health is seeking a Machine Learning Engineer to contribute to a special project focused on expanding access to ultrasound technology while advancing our next-generation ...

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and ...

As a Machine Learning Engineer Lead, you will join our Data Science & AI Pod, focused on designing, building, and deploying enterprise-wide AI and machine learning solutions that support business ...

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

Machine Learning engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

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Machine Learning Engineer Opt information

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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

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

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

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

Infographic showing various Machine Learning Engineer Opt job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

NTENT

Toronto, ON • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 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.