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Aws Machine Learning Jobs in Ontario (NOW HIRING)

Quincus

Machine Learning Engineer

Toronto, ON

... 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 ...

Bree

Machine Learning Engineer

Toronto, ON · On-site

$100 - $130/hr

  • Dental

  • Vision

  • PTO

Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and ... Strong understanding of machine learning algorithms, including supervised and unsupervised learning ...

ALS

Junior Machine Learning Engineer

Waterloo, ON · On-site

CA$80K - CA$95K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Junior Machine Learning Engineer on the Global AI Team, you will support the design ... GCP), and AWS, with a preference for Azure and GCP. * Assist in building model pipelines ...

Autodesk

Machine Learning Ops Developer

Toronto, ON

Experience with cloud platforms, especially AWS or Azure, for deploying and managing machine learning infrastructure * Database Knowledge: Familiarity with databases and data storage solutions ...

KPMG

Manager, ML/AI Engineer, Data & AI

Toronto, ON

Cloud AI / ML certifications (e.g., Azure AI Engineer Associate or better, AWS Machine Learning Specialty or better, Google Professional ML Engineer or better, Databricks ML Engineer Associate or ...

KPMG

Manager, ML/AI Engineer, Data & AI

Toronto, ON

Cloud AI / ML certifications (e.g., Azure AI Engineer Associate or better, AWS Machine Learning Specialty or better, Google Professional ML Engineer or better, Databricks ML Engineer Associate or ...

TheAppLabb

Sr. Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful ... Hands-on experience with AWS, Azure or GCP. * Expertise in Kubernetes, Docker, and workflow ...

Td

Research Machine Learning Scientist

Toronto, ON · On-site

CA$140K - CA$250K/yr

We develop and deploy industry-leading machine learning systems that impact the lives of over 27 ... Familiarity with cloud computing systems like Azure or AWS * Experience in LLM post-training and ...

United Airlines

Senior Machine Learning Engineer

Mississauga, ON · On-site

CA$105K - CA$125K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Required Skills Azure data factory, Azure data bricks, Azure Machine Learning, PySpark, SQL, Python, PB, AWS, SF, DEVOPS and Azure Security - Create and maintain optimal data pipeline architecture ...

United Airlines

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$105K - CA$125K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Required Skills Azure data factory, Azure data bricks, Azure Machine Learning, PySpark, SQL, Python, PB, AWS, SF, DEVOPS and Azure Security - Create and maintain optimal data pipeline architecture ...

Autodesk

Job Requisition ID # 26WD98709 Senior Software Engineer - Machine Learning Fusion - Collaborative ... Experience with cloud data processing, training, deployment, or operations (AWS, GCP) * Experience ...

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All JobsAws Machine Learning JobsAws Machine Learning Jobs in Ontario

Aws Machine Learning information

See Ontario salary details

$24K

$127.8K

$211K

How much do aws machine learning jobs pay per year?

As of Aug 16, 2026, the average yearly pay for aws machine learning in Ontario is $127,790.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,500.00 and $162,000.00 per year, depending on experience, location, and employer.

What is an AWS Machine Learning?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

What does an AWS Machine Learning do?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.

What are the key skills and qualifications needed for an AWS Machine Learning?

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

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

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

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

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

Aws Machine Learning jobs near you
Infographic showing various Aws Machine Learning job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $127,790 per year, or $61.4 per hour.

Machine Learning Engineer

Quincus

Toronto, ON

Full-time

Re-posted 13 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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