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Artificial Intelligence Machine Learning Engineer Jobs in Toronto, ON

Quincus

Machine Learning Engineer

Toronto, ON · On-site

As a machine learning engineer, you will be responsible for designing and implementing scalable ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Clio

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 ... use artificial intelligence to improve all of our operations. In recruitment, AI helps us ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

Analytics, Insights, & Artificial Intelligence Pay Details: $120,000 - $250,000 CAD The pay details ... As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Analytics, Insights, & Artificial Intelligence Pay Details: $154,000 - $199,500 CAD The pay details ... Day-to-day as a Machine Learning Engineer: * Join a world-class team of AI developers with an ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

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 ...

Bmo

Machine Learning Engineer

Toronto, ON · On-site

CA$82K - CA$154K/yr

Data Analytics & Reporting Researches, builds, and implements scalable artificial intelligence ... Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models.

New

Manulife

Machine Learning Engineer

Toronto, ON · On-site

As a Machine Learning Engineer, you will design, build, and operate the platforms, pipelines, and ... We use data and analytics technologies, such as artificial intelligence (AI), and automated ...

New

Boson AI

Machine Learning Engineer - Enterprise

Toronto, ON · On-site

CA$150K - CA$400K/yr

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a ... Proficiency in programming languages (e.g., Python, Rust, TypeScript or Go) and relevant ML ...

Td

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - CA$250K/yr

Analytics, Insights, & Artificial Intelligence Pay Details: $170,000 - $250,000 CAD The pay details ... As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ...

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

... artificial intelligence, machine learning, computer vision, and self-driving technologies, and apply insights from the literature. - Work with large datasets from various sources as well as Waabi ...

Bree

Machine Learning Engineer

Toronto, ON · On-site

$100 - $130/hr

Apply machine learning design patterns to build modular, reusable, and production-ready models. * Collaborate with data engineers to develop high-performance data pipelines for training and inference.

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Artificial Intelligence Machine Learning Engineer information

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

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

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

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

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

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

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

What cities near Toronto, ON are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Toronto, ON with the most Artificial Intelligence Machine Learning Engineer job openings:

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 100% Full Time. Highlights an 81% In-person, and 19% Remote job distribution.

Machine Learning Engineer

Quincus

Toronto, ON • On-site

Full-time

Re-posted 16 days ago

Job description

"Make every logistics journey your best one yet"

The Company.
Founded in 2014, Quincus is a B2B supply chain operating SaaS platform headquartered in Singapore. We solve today's global supply chain challenges with groundbreaking technology. Using AI and machine learning, we have digitized and optimized the logistics process while giving customers full transparency into their supply chain. 
 
Quincus was founded by two visionary entrepreneurs who possess more than a decade of experience in tech. Chief Product Officer Katherina-Olivia Lacey is leading a tech revolution in this space while empowering women in the supply chain industry. Jonathan E. Savoir, Chief Executive Officer, appeared on Forbes' 30 Under 30 Asia List in 2020, and also serves on the boards of several startups.  

Overview.
Quincus Research is building the next generation of intelligent systems for all Quincus products. To achieve this, we're working on projects that utilize the latest computer science techniques developed by skilled software engineers and research scientists. Quincus Research teams collaborate closely with other teams across Quincus, maintaining the flexibility and versatility required to adapt new projects and focuses that meet the demands of the world's fast-paced business needs. 

Job Overview. 
We are looking for a highly motivated and experienced machine learning engineer to join our team and help us develop and deploy deep learning and reinforcement learning algorithms at scale. 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. 

Responsibilities: 
- Design and implement scalable systems for serving deep learning and reinforcement learning models.
- Optimize inference performance of deep learning and reinforcement learning models using techniques such as quantization, pruning, and distillation.
- Utilize GPU computing to accelerate model training and inference.
- Develop and deploy production workflows for training and serving machine learning models.
- Collaborate with data scientists and software engineers to design and implement machine learning systems.
- Monitor and improve the performance of machine learning models in production.
- Stay up-to-date with the latest research and techniques in deep learning and reinforcement learning. 
 
Qualifications:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- 3+ years of experience in software engineering or machine learning engineering.
- Strong programming skills in Python (C++ or Java a plus)
- Experience with deep learning frameworks such as TensorFlow or PyTorch.
- Experience with GPU programming using CUDA, OpenCL, or similar libraries.
- Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS. 

Preferred Qualifications: 
- Ph.D. in Computer Science, Electrical Engineering, or a related field.
- 5+ years of experience in software engineering or machine learning engineering.
- Experience with reinforcement learning algorithms and frameworks.
- Experience with production deployment of machine learning models and implementation of APIs for big data.
- Strong understanding of computer architecture and performance optimization.
- Strong communication and collaboration skills. 

If you are passionate about developing and deploying machine learning algorithms at scale, and want to join a dynamic team working on cutting-edge technology, we encourage you to apply for this position.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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