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Applied Machine Learning Jobs in Ontario (NOW HIRING)

Socotra, Inc.

Machine Learning Engineer

Toronto, ON · On-site

$118.80 - $148.50/hr

Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the ... We operate at the intersection of applied ML and real business impact, shipping models that ...

Ideogram

Machine Learning Engineer, Applied AI

Toronto, ON · On-site

$80 - $110/hr

The Opportunity As an Applied ML Engineer at Ideogram, you'll bridge research and product - turning ... A culture of learning and growth, where curiosity is encouraged and mentorship is part of the ...

Td

Senior Machine Learning Engineer

Toronto, ON

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 ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/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 ...

Td

Machine Learning Engineer II

Toronto, ON

CA$154K - CA$199K/yr

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Our team is building standardized frameworks to launch AI models that have real ...

Fullscript

Staff, Machine Learning Engineer

Toronto, ON · On-site +1

The Opportunity We're hiring a Staff Machine Learning Engineer to join our AI team and help shape ... Experience with recommendation systems, personalization, or other applied ML systems beyond LLMs

Fullscript

Staff, Machine Learning Engineer

Ottawa, ON · On-site +1

The Opportunity We're hiring a Staff Machine Learning Engineer to join our AI team and help shape ... Experience with recommendation systems, personalization, or other applied ML systems beyond LLMs

Autodesk

We are a small, agile applied research team that are intensely curious and passionate about the ... We see many opportunities for machine learning to expand what our customers are capable of. In this ...

Future Secure AI

Evaluate machine learning models for understanding user intent, predicting workflow needs, and ... as an Applied Scientist, Data Scientist, or Machine Learning Engineer * Bachelor's degree in ...

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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 a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Compensation at this level reflects significant expertise, responsibility, and impact on business or product development.

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 strong 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 engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries or companies can earn $500,000 or more annually. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of successful projects in applied machine learning environments.

Will MLE be replaced by AI?

Applied Machine Learning (MLE) professionals design, develop, and implement machine learning models, which are essential for AI systems. While AI automation tools can assist or streamline certain tasks, MLE roles focus on model development, data preprocessing, and system integration that require specialized expertise, making complete replacement unlikely in the near term.
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 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution.

Machine Learning Engineer (Toronto)

United States Digital Space LLC

Toronto, ON • On-site

$100 - $130/hr

Other

Posted 8 days ago

Job description

Machine Learning Engineer – Emerging Technology

The company’s Emerging Technology team is seeking a Machine Learning Engineer to join a team focused on building and supporting Generative AI, Machine Learning (ML), and Data Science solutions across the organization. This position could be based in our Chicago or Toronto offices.

Objectives
  • Implement AI & ML technology in collaboration with business partners and product owners
  • Develop and support enterprise‑level AI exploration tools and capabilities
  • Provide guidance and support for safe development and deployment of AI
  • Establish and maintain policies, guidelines, and processes for AI/ML governance, including third‑party AI governance
Responsibilities
  • Work closely with product squads and partner teams to design, build, integrate, and deploy ML and GenAI solutions in production, while sharing best practices with other engineers.
  • Communicate ML and GenAI concepts clearly to technical and non‑technical stakeholders, with a focus on practical application to use cases.
  • Collaborate with engineers, data scientists, and product partners to develop and deploy ML and GenAI solutions that deliver measurable business value.
  • Partner with data scientists and domain experts to identify practical opportunities where data, ML, and GenAI can improve business outcomes.
  • Build scalable services, pipelines, and workflows for ML and GenAI use cases, with guidance from senior engineers where needed.
  • Support production applications by helping maintain reliability, monitoring performance, and using metrics to improve existing ML solutions.
  • Use cloud services, primarily in AWS, to support data pipelines, model deployment, and LLM‑based workflows. Familiarity with Azure services is a plus.
  • Use Python and large‑scale workflow orchestration tools (for example, Airflow) to build production‑quality services, data pipelines, and integrations across diverse data sources and storage systems.
Qualifications
  • 3+ years of experience as a machine learning engineer or in a closely related software engineering role focused on ML systems.
  • Experience writing production‑quality Python code and applying sound software engineering practices.
  • Strong foundation in machine learning concepts and practical experience applying modern ML techniques to real‑world problems.
  • Strong software engineering fundamentals, including code quality, automated testing, version control, observability, and performance optimization.
  • Experience building or integrating Generative AI applications, such as retrieval‑augmented generation, evaluation workflows, or agent‑assisted systems.
  • Experience building or improving search, retrieval, or data access layers that support ML or GenAI applications.
  • Experience with containerized deployment and orchestration, such as Docker and Kubernetes.
  • Experience with cloud‑native ML and data services, especially in AWS. Familiarity with tools such as Bedrock, S3, SageMaker, Azure AI Search, or Azure OpenAI is helpful.
  • Bachelor’s degree in computer science, machine learning, data science, applied mathematics, or a related field, or equivalent practical experience.
What Would Make You Stand Out
  • Passion for using data and ML to drive better business outcomes for customers
  • Proven ability to work effectively in a distributed team environment and contribute in fast‑paced settings.
  • Familiarity with credit ratings agencies, regulations, and data products
  • Excellent written and verbal communication skills
  • Advocate of good code quality and architectural practices
  • Strong interpersonal skills and ability to work proactively as a team player
Compensation (Toronto)

Expected base pay rates for the role will be between $100,000 and $130,000 CAD per year. Actual salaries will be determined on an individualized basis and may vary based on factors including but not limited to education, training, experience, past performance, and other job‑related factors. Base pay is one part of the company’s total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, long‑term incentives, and other benefits sponsored by the company.

EEO Statement

The company is proud to be an Equal Opportunity and Affidavit of Good Faith Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.

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