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Healthcare Machine Learning Jobs in Ontario (NOW HIRING)

Tobermory

Machine Learning Engineer

Richmond Hill, ON · On-site

CA$76K - CA$138K/yr

Health coverage, dental care, vision coverage, life insurance, disability protection, RRSP matching ... Machine Learning Engineer, NVH is a machine learning and software engineering role within Tesla ...

New

Td

Machine Learning Engineer

Toronto, ON · On-site

CA$120K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ... health and well-being benefits, savings and retirement programs, paid time off, banking benefits ...

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 ... Competitive, equitable salary with top-tier health benefits, dental, and vision insurance * Hybrid ...

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 ... health and well-being benefits, savings and retirement programs, paid time off, banking benefits ...

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All JobsHealthcare Machine Learning JobsHealthcare Machine Learning Jobs in Ontario

Healthcare Machine Learning information

See Ontario salary details

$22K

$120.3K

$176K

How much do healthcare machine learning jobs pay per year?

As of Sep 14, 2026, the average yearly pay for healthcare machine learning in Ontario is $120,316.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $165,000.00 per year, depending on experience, location, and employer.

What is a healthcare machine learning?

A Healthcare Machine Learning job involves developing and applying machine learning models to analyze medical data and improve healthcare outcomes. Professionals in this role work with electronic health records, medical imaging, genomics, and other healthcare data to assist in disease prediction, diagnosis, and personalized treatments. They collaborate with clinicians, data scientists, and engineers to ensure models are clinically relevant and ethically sound. Strong knowledge of machine learning, data preprocessing, and regulatory compliance (such as HIPAA) is essential.

What are the key skills and qualifications needed to thrive in healthcare machine learning?

To thrive in Healthcare Machine Learning, you need strong expertise in data science, machine learning algorithms, and biomedical informatics, often supported by an advanced degree in computer science, statistics, or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and healthcare data standards (like HL7 or FHIR) is highly beneficial, and certifications in data science or health informatics can provide an edge. Excellent problem-solving skills, attention to detail, and the ability to communicate complex technical concepts to diverse healthcare teams are valuable soft skills. These competencies are vital for developing robust, ethically sound machine learning solutions that improve clinical decision-making and patient outcomes.

What are some common challenges faced by professionals working in healthcare machine learning?

Professionals in Healthcare Machine Learning often encounter challenges such as navigating complex, unstructured, or incomplete healthcare data while ensuring strict compliance with privacy regulations like HIPAA. They must also bridge the gap between technical requirements and clinical needs, collaborating closely with medical professionals who may not have a technical background. Additionally, validating and interpreting machine learning models for real-world clinical use adds another layer of complexity, as solutions must be both accurate and explainable. Overcoming these challenges requires strong technical skills, effective teamwork, and a commitment to ethical, patient-centered solutions.

What does machine learning do in healthcare?

Healthcare machine learning involves developing algorithms that analyze medical data to assist in diagnosis, treatment planning, and predicting patient outcomes. Professionals in this field use tools like Python and TensorFlow, and often require knowledge of medical terminology and data privacy regulations to improve healthcare delivery.

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

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

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

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

Healthcare Machine Learning jobs near you
Infographic showing various Healthcare Machine Learning job openings in Ontario as of September 2026, with employment types broken down into 2% As Needed, 52% Full Time, 24% Part Time, and 22% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $120,316 per year, or $57.8 per hour.

Machine Learning Engineer

Richmond Hill, ON • On-site

Tobermory
See more jobs at Tobermoryexternal

CA$76K - CA$138K/yr

Other

Medical, Dental, Vision, Life, PTO

Posted 3 days ago

New

Job description

Machine Learning Engineer, NVH develops advanced machine learning systems that help Tesla improve product diagnostics and quality across its vehicles and technologies. Based in Richmond Hill, this role combines artificial intelligence, audio processing and engineering to create tools that support manufacturing and customer satisfaction.

The role is about building diagnostic models, managing those data pipelines and getting machine learning solutions out of the lab and into real production environments. You will work across teams in manufacturing, quality and vehicle engineering and the work feeds straight into how Tesla spots product issues and tackles them at scale.

Tesla gives you the chance to engage with tough technology that really affects its products and customers world wide. Check the job details below to get more context.

Company Name : Tesla
Location : Richmond Hill, Ontario, Canada
Salary : $76,000 – $138,000/annually
Job Type : Full time
Start date : As soon as possible
Benefits : Health coverage, dental care, vision coverage, life insurance, disability protection, RRSP matching contributions, employee stock purchase plan, employee assistance resources, parental support programs, paid sick leave, vacation time, paid holidays, Tesla family benefits, product savings, wellness discounts and additional employee rewards.

Job Description
  • Machine Learning Engineer, NVH is a machine learning and software engineering role within Tesla’s Noise, Vibration and Harshness team.
  • This is a full time position based in Richmond Hill, Ontario.
  • The role focuses on developing diagnostic systems for Tesla vehicles and products.
  • The position combines machine learning, audio processing and production deployment work.
  • The work environment is research driven, technology focused and team oriented.
  • Employees receive competitive compensation, stock awards, benefits and access to innovative engineering projects.
Responsibilities
  • Design, develop and deploy machine learning models and audio algorithms for NVH diagnostics.
  • Build and maintain machine learning pipelines from data collection through production deployment.
  • Work with manufacturing, quality audit and vehicle engineering teams to integrate diagnostic systems.
  • Improve model performance through testing, experimentation and iterative development.
  • Develop tools and frameworks for collecting data, labelling and model monitoring.
  • Work to develop coding standards, testing practices, documentation and reproducibility.
  • Review developments in audio machine learning, signal processing and deep learning.
  • Apply relevant research advancements to Tesla’s diagnostic challenges.
Requirements
  • A degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science or a related field is required, or equivalent work background.
  • Strong knowledge of Python and C++ is required.
  • Solid background in software engineering practices including version control, testing and code review is required.
  • Strong knowledge of machine learning fundamentals including neural networks, optimization methods, regularization and model evaluation is required.
  • Work background with neural network architectures for audio applications including CNNs, RNNs and Transformers is required.
  • Strong knowledge of event detection and of classification models.
  • Skilled in PyTorch or another major deep learning tool such as TensorFlow.
  • Can work with machine learning systems from development through deployment in production environments.
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