Salary for Entry-level / Junior Machine Learning Engineer in Canada during 2024

Salary details

The average entry-level / junior Machine Learning Engineer salary lies between USD 105,300 and USD 157,900 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.

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: Dec. 22, 2024

Top 20 Job Tags for Entry-level / Junior Machine Learning Engineer roles

The three most common job tag items assiciated with entry-level / junior Machine Learning Engineer job listings are Machine Learning, Engineering and Computer Science. 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 | 654 jobs Engineering | 427 jobs Computer Science | 400 jobs Python | 392 jobs Research | 271 jobs NLP | 250 jobs PhD | 237 jobs PyTorch | 212 jobs E-commerce | 211 jobs Deep Learning | 208 jobs TensorFlow | 195 jobs ML models | 176 jobs Statistics | 173 jobs LLMs | 168 jobs Computer Vision | 148 jobs Java | 123 jobs Pipelines | 118 jobs Mathematics | 116 jobs Spark | 111 jobs Privacy | 110 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Machine Learning Engineer roles

The three most common job benefits and perks assiciated with entry-level / junior Machine Learning Engineer job listings are Career development, Health care and Team events. 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 | 551 jobs Health care | 243 jobs Team events | 207 jobs Startup environment | 201 jobs Medical leave | 185 jobs Equity / stock options | 161 jobs Conferences | 118 jobs Flex vacation | 117 jobs Parental leave | 116 jobs Flex hours | 112 jobs Insurance | 108 jobs 401(k) matching | 107 jobs Flexible spending account | 92 jobs Competitive pay | 82 jobs Salary bonus | 56 jobs Transparency | 49 jobs Travel | 17 jobs Lunch / meals | 11 jobs Wellness | 11 jobs Relocation support | 11 jobs

Salary Composition

The salary for an entry-level or junior machine learning engineer in Canada typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and your individual performance. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and paid time off. The composition can vary based on the region, with tech hubs like Toronto or Vancouver potentially offering higher salaries. Industry also plays a role; for instance, finance and tech industries might offer more competitive packages compared to academia or non-profits. Larger companies might provide more comprehensive benefits and bonuses compared to smaller startups, which might offer more equity-based compensation.

Next Steps for Salary Increase

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand, such as deep learning, natural language processing, or computer vision. Pursuing a master's degree or Ph.D. in a related field can also enhance your qualifications and open up higher-paying opportunities. Networking within the industry and attending conferences can help you stay updated on the latest trends and technologies, making you more valuable to employers. Additionally, gaining experience in managing projects or leading teams can position you for roles with greater responsibility and higher pay. Seeking opportunities in high-demand industries or regions can also lead to salary increases.

Educational Requirements

Most entry-level machine learning engineer positions require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. A strong foundation in mathematics, particularly in linear algebra, calculus, and probability, is essential. Some positions may prefer candidates with a master's degree, especially if the role involves more complex machine learning tasks or research. Practical experience through internships, projects, or contributions to open-source projects can also be highly beneficial.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise in machine learning. Some popular certifications include:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications can validate your skills in specific platforms or tools and show your commitment to professional development.

Required Experience

For an entry-level position, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or personal projects. Experience with programming languages such as Python or R, and familiarity with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn, is often expected. Demonstrating experience in data preprocessing, model training, and evaluation can also be advantageous.

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