Salary for Mid-level / Intermediate Engineer in Canada during 2024

Salary details

The average mid-level / intermediate Engineer salary lies between USD 84,615 and USD 140,000 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.

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. 15, 2024

Top 20 Job Tags for Mid-level / Intermediate Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Engineer job listings are Engineering, Python and Machine Learning. 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:

Engineering | 10757 jobs Python | 10435 jobs Machine Learning | 6977 jobs Computer Science | 6643 jobs SQL | 6517 jobs Pipelines | 5886 jobs AWS | 5275 jobs Architecture | 4855 jobs Security | 4415 jobs Testing | 3968 jobs Azure | 3741 jobs ETL | 3722 jobs Agile | 3709 jobs Data pipelines | 3581 jobs Java | 3324 jobs Research | 3216 jobs Spark | 2965 jobs GCP | 2734 jobs Big Data | 2729 jobs APIs | 2599 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Engineer job listings are Career development, Health care and Flex hours. 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 | 9271 jobs Health care | 4909 jobs Flex hours | 3392 jobs Equity / stock options | 3262 jobs Competitive pay | 2887 jobs Startup environment | 2832 jobs Team events | 2301 jobs Flex vacation | 2081 jobs Insurance | 2053 jobs Salary bonus | 1937 jobs Medical leave | 1925 jobs Parental leave | 1855 jobs Wellness | 1271 jobs 401(k) matching | 1088 jobs Relocation support | 660 jobs Conferences | 599 jobs Home office stipend | 566 jobs Unlimited paid time off | 462 jobs Fitness / gym | 452 jobs Transparency | 431 jobs

Salary Composition

In Canada, the salary composition for a mid-level AI/ML/Data Science engineer typically includes a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and your individual performance, often ranging from 5% 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 can vary by region, with tech hubs like Toronto and Vancouver offering higher base salaries but potentially lower bonuses compared to smaller cities. Industry also plays a role; for instance, finance and tech sectors might offer more lucrative bonuses compared to academia or public sector roles. Larger companies often provide more structured and predictable compensation packages, while startups might offer lower base salaries but higher equity stakes.

Increasing Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open doors to higher-paying roles and leadership positions.
• Networking: Engage with professional networks and communities. Attending conferences, meetups, and workshops can lead to new opportunities and insights into industry trends.
• Certifications: Obtain advanced certifications that are recognized in the industry to demonstrate your expertise and commitment to professional growth.
• Leadership Roles: Seek opportunities to lead projects or teams, as managerial roles often come with higher compensation.

Educational Requirements

For a mid-level AI/ML/Data Science position, a bachelor's degree in computer science, data science, mathematics, statistics, or a related field is typically required. Many employers prefer candidates with a master's degree, especially for roles that involve complex problem-solving and advanced algorithm development. A strong foundation in mathematics, particularly in linear algebra, calculus, and probability, is essential. Additionally, coursework or experience in programming languages such as Python, R, or Java, and familiarity with machine learning frameworks like TensorFlow or PyTorch, are often expected.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Data Science Council of America (DASCA) Certifications

These certifications can validate your skills in specific tools and platforms, making you a more attractive candidate for employers.

Required Experience

Typically, a mid-level AI/ML/Data Science role requires 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, model development, and deployment. Experience in handling large datasets, using machine learning algorithms, and working with data visualization tools is often expected. Additionally, experience in a specific industry, such as finance, healthcare, or e-commerce, can be advantageous, as it provides domain-specific insights that are valuable in developing tailored AI solutions.

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