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Applied Machine Learning Jobs in Ontario (NOW HIRING)

StackAdapt

Applied Machine Learning Scientist

London, ON · On-site +1

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 ...

Td

Applied Machine Learning Scientist I

Toronto, ON · On-site

CA$105K - CA$125K/yr

Additional 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 ...

Td

Applied Machine Learning Scientist I

Toronto, ON · On-site +1

CA$105K - CA$125K/yr

About the Role We are looking for a highly motivated Applied Machine Learning Scientist to join the Wealth AI / ML Practice, focused on Generative AI and Agentic Capabilities. In this role, you will ...

Td

Applied Machine Learning Scientist II

Toronto, ON · On-site

CA$125K - CA$154K/yr

About the Role We are looking for a highly motivated Applied Machine Learning Scientist II to join the Wealth AI / ML Practice, focused on Generative AI and Agentic Capabilities. In this role, you ...

Td

Applied Machine Learning Scientist II

Toronto, ON · On-site

CA$125K - CA$154K/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 ...

Themis

Machine Learning Engineer

Mississauga, ON

CA$85K - CA$135K/yr

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 ...

Td

Machine Learning Engineer

Toronto, ON · 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 ...

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Applied Machine Learning information

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.

What are the key skills and qualifications needed to thrive as an applied machine learning professional?

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 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:
Applied Machine Learning jobs near you
Infographic showing various Applied Machine Learning job openings in Ontario as of July 2026, with employment types broken down into 77% Full Time, 22% Part Time, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Applied Machine Learning Scientist

StackAdapt

London, ON • On-site, Remote

Other

Re-posted 28 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.
 
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-science 
Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU
 
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

Apply