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Applied Machine Learning Jobs in Ontario (NOW HIRING)

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers ...

Applied Machine Learning Scientist I

Toronto, ON ยท On-site +1

CA$81K - CA$115K/yr

We're looking for a highly motivated Applied Machine Learning Scientist to join our AI2 team. In this role, you'll drive the development and deployment of ML solutions that power data-driven decision ...

Machine Learning Engineer About Themis Intelligence Themis Intelligence builds the Utility ... We work at the frontier of applied AI, building models and data systems that integrate time-series ...

Proven capability and a sound understanding of engineering principles as applied to the following areas: * Machine Learning and AI * Advanced capability in multiple computer programming languages

Machine Learning Engineer

Toronto, ON ยท On-site

CA$120K - CA$250K/yr

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Work with large-scale, real-world datasets spanning multiple modalities ...

What You'll Need to Succeed To be considered, you'll need strong hands-on experience as a Machine Learning Engineer with deep exposure to time series forecasting and applied ML in production settings.

Senior Machine Learning Engineer

Toronto, ON ยท On-site

CA$170K - CA$250K/yr

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Work with large-scale, real-world datasets spanning multiple modalities ...

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Applied Machine Learning information

Which 3 jobs will survive AI?

Applied Machine Learning professionals, data scientists, and AI system engineers are likely to continue thriving as AI advances, due to their expertise in developing, managing, and interpreting complex models. These roles require specialized skills in programming, statistical analysis, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with new tools like TensorFlow or PyTorch are essential for long-term job security in this field.

What are the typical collaboration dynamics between Applied Machine Learning engineers and other teams within a company?

Applied Machine Learning engineers often work closely with cross-functional teams including data scientists, software engineers, product managers, and business analysts. They are typically responsible for translating business problems into machine learning solutions and ensuring models are effectively integrated into production systems. This role requires frequent communication to align on project goals, share progress, and address technical challenges, making teamwork and stakeholder management crucial for successful deployments and continuous improvement.

What is applied machine learning?

Applied machine learning involves using machine learning techniques and algorithms to solve real-world problems in various industries, such as healthcare, finance, and technology. Practitioners focus on selecting appropriate models, preparing data, training algorithms, and deploying solutions that deliver tangible value. Unlike theoretical machine learning, applied machine learning emphasizes practical implementation, evaluation, and optimization to meet business or research objectives.

Is applied AI a good career?

Applied machine learning is a growing field with high demand for professionals skilled in algorithms, programming, and data analysis. It offers opportunities in various industries such as technology, healthcare, and finance, often requiring knowledge of tools like Python, TensorFlow, and cloud platforms. The career can be rewarding with continuous learning and development of specialized skills.

What are the key skills and qualifications needed to thrive as an Applied Machine Learning professional, and why are they important?

To excel in Applied Machine Learning, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a relevant degree or certification. Familiarity with programming languages like Python or R, frameworks such as TensorFlow or PyTorch, and version control systems is typically required. Strong problem-solving abilities, communication skills, and a collaborative mindset help you interpret results and convey insights to diverse stakeholders. These competencies are crucial for building effective models, driving data-driven decisions, and ensuring the successful integration of machine learning solutions into real-world applications.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying scalable AI systems can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires strong programming skills, knowledge of cloud platforms, and a track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. Such roles usually involve leadership responsibilities, strategic planning, and may require multiple years of industry experience and relevant certifications.
What are popular job titles related to Applied Machine Learning jobs in Ontario? For Applied Machine Learning jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Applied Machine Learning jobs in Ontario look for? The top searched job categories for Applied Machine Learning jobs in Ontario are:
Infographic showing various Applied Machine Learning job openings in Ontario as of June 2026, with employment types broken down into 1% Internship, 3% As Needed, 70% Full Time, 19% Part Time, 6% Temporary, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Applied Machine Learning Scientist

StackAdapt

London, ON โ€ข On-site, Remote

Other

Posted 5 days ago


Job description

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.
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Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/
Learn more about our team culture here: https://www.stackadapt.com/careers/data-scienceย 
Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU
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StackAdapt is a Remote First company, and we are open to candidates located anywhere in the UK, Ireland and Germany for this position.
What you'll be doing:
  • Innovate ML algorithms to maximize ROI and advertising performance. This ranges from creating entirely new algorithms, to improvements on state-of-the art methods, to development using a deep understanding of classic methods
  • Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms
  • Prototype potential algorithms and pipelines, test them using historical data, and iterate to modify based on insights
What you'll bring to the table:
  • Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
  • Have the ability to take an ambiguously defined task, and break it down into actionable steps
  • Have a comprehensive understanding of statistics, optimization and machine learning
  • Are proficient in coding, data structures, and algorithms
  • Enjoy working in a friendly, collaborative environment with others