Machine Learning Developer Salary in Canada during 2024
💰 The median Machine Learning Developer Salary in Canada during 2024 is USD 128,300
✏️ This salary info is based on 14 individual salaries reported during 2024
Salary details
The average Machine Learning Developer salary lies between USD 95,000 and USD 135,000 in Canada. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.
- Job title
- Machine Learning Developer
- Experience
- all levels
- Region
- Canada
- Salary year
- 2024
- Sample size
- 14
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Top 20 Job Tags for Machine Learning Developer roles
The three most common job tag items assiciated with Machine Learning Developer job listings are Machine Learning, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:
Machine Learning | 86 jobs Python | 75 jobs Engineering | 63 jobs ML models | 54 jobs Research | 46 jobs AWS | 43 jobs Computer Science | 42 jobs PyTorch | 38 jobs Architecture | 38 jobs TensorFlow | 35 jobs Testing | 33 jobs Deep Learning | 30 jobs Statistics | 27 jobs Scikit-learn | 25 jobs Pipelines | 25 jobs Data analysis | 24 jobs GCP | 21 jobs Azure | 20 jobs Security | 19 jobs LLMs | 19 jobsTop 20 Job Perks/Benefits for Machine Learning Developer roles
The three most common job benefits and perks assiciated with Machine Learning Developer job listings are Career development, Health care and Competitive pay. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:
Career development | 73 jobs Health care | 30 jobs Competitive pay | 22 jobs Flex hours | 21 jobs Flex vacation | 18 jobs Team events | 16 jobs Equity / stock options | 15 jobs Salary bonus | 13 jobs Medical leave | 12 jobs Startup environment | 11 jobs Parental leave | 9 jobs Insurance | 7 jobs Transparency | 5 jobs Conferences | 5 jobs Home office stipend | 5 jobs Flexible spending account | 3 jobs Wellness | 2 jobs Travel | 2 jobs Gear | 2 jobs Snacks / Drinks | 2 jobsSalary Composition for Machine Learning Developers in Canada
The salary for a Machine Learning Developer in Canada typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, and comprehensive benefits packages that cover health, dental, and retirement plans.
The composition of the salary can vary based on several factors:
- Region: Salaries in major tech hubs like Toronto or Vancouver might be higher due to the cost of living and demand for tech talent.
- Industry: Companies in finance or healthcare might offer higher salaries compared to those in education or non-profit sectors.
- Company Size: Larger companies often provide more comprehensive benefits and bonuses, while startups might offer equity as part of the compensation package.
Steps to Increase Salary from a Machine Learning Developer Position
To increase your salary from a Machine Learning Developer position, consider the following strategies:
- Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as natural language processing, computer vision, or reinforcement learning, which are in high demand.
- Pursue Advanced Education: Obtaining a master's or Ph.D. in a relevant field can open up higher-paying opportunities and leadership roles.
- Gain Leadership Experience: Transitioning into roles like a team lead or project manager can increase your earning potential.
- Network and Build a Personal Brand: Attend industry conferences, contribute to open-source projects, and publish research to enhance your visibility and reputation in the field.
- Negotiate Offers: When changing jobs, negotiate your salary and benefits package to reflect your experience and the value you bring to the company.
Educational Requirements for Machine Learning Developers
Most Machine Learning Developer positions require at least a bachelor's degree in computer science, data science, mathematics, or a related field. However, many employers prefer candidates with a master's degree or Ph.D., especially for roles involving complex research and development tasks. A strong foundation in mathematics, statistics, and programming is essential, as these skills are critical for developing and implementing machine learning models.
Helpful Certifications for Machine Learning Developers
While not always required, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:
- Google Professional Machine Learning Engineer
- AWS Certified Machine Learning – Specialty
- Microsoft Certified: Azure AI Engineer Associate
- TensorFlow Developer Certificate
These certifications validate your skills in specific platforms and tools, making you a more attractive candidate for employers using these technologies.
Experience Requirements for Machine Learning Developers
Typically, employers look for candidates with at least 2-5 years of experience in machine learning or related fields. This experience should include hands-on work with machine learning algorithms, data analysis, and software development. Experience with popular machine learning frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Additionally, experience in deploying machine learning models in production environments is highly valued.
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