Software Engineer Salary in Canada during 2024

Salary details

The average Software Engineer salary lies between USD 120,000 and USD 199,700 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: Jan. 19, 2025

Top 20 Job Tags for Software Engineer roles

The three most common job tag items assiciated with Software 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 | 8922 jobs Python | 8801 jobs Machine Learning | 7466 jobs Computer Science | 6716 jobs Architecture | 4754 jobs Java | 4370 jobs AWS | 3909 jobs Testing | 3885 jobs Security | 3717 jobs Pipelines | 3068 jobs APIs | 2929 jobs Kubernetes | 2907 jobs SQL | 2838 jobs Research | 2797 jobs Agile | 2703 jobs Azure | 2456 jobs JavaScript | 2207 jobs Docker | 2134 jobs Privacy | 2129 jobs GCP | 2125 jobs

Top 20 Job Perks/Benefits for Software Engineer roles

The three most common job benefits and perks assiciated with Software Engineer job listings are Career development, Health care and Equity / stock options. 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 | 8577 jobs Health care | 4752 jobs Equity / stock options | 4641 jobs Startup environment | 2910 jobs Competitive pay | 2724 jobs Flex hours | 2660 jobs Salary bonus | 2592 jobs Medical leave | 2489 jobs Flex vacation | 2264 jobs Insurance | 2151 jobs Parental leave | 1969 jobs Team events | 1836 jobs 401(k) matching | 1436 jobs Wellness | 1222 jobs Relocation support | 737 jobs Fertility benefits | 541 jobs Transparency | 514 jobs Unlimited paid time off | 496 jobs Home office stipend | 478 jobs Flexible spending account | 472 jobs

Salary Composition

In Canada, the salary composition for AI/ML/Data Science roles can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In major tech hubs like Toronto or Vancouver, the base salary might be higher due to the cost of living and competition for talent.

• Bonuses: These are performance-based and can vary widely. In larger tech companies or financial institutions, bonuses can be substantial, sometimes up to 20-30% of the base salary, depending on individual and company performance.

• Additional Remuneration: This includes stock options, restricted stock units (RSUs), and other benefits like health insurance, retirement plans, and wellness programs. Startups might offer more equity to compensate for a lower base salary, while established companies might provide a more balanced package.

Increasing Salary

To increase your salary from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing a master's or Ph.D. in a related field can open doors to higher-paying roles, especially in research or leadership positions.

• Networking and Industry Engagement: Attend conferences, workshops, and meetups to connect with industry leaders and peers. This can lead to new opportunities and insights into higher-paying roles.

• Leadership Roles: Aim for managerial or lead positions within your team or company. Leadership roles often come with higher compensation packages.

Educational Requirements

Most AI/ML/Data Science roles require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for research-intensive positions. These advanced degrees provide a deeper understanding of complex algorithms and data analysis techniques, which are crucial for high-level roles.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and skill set:

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

These certifications demonstrate proficiency in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in software engineering, data analysis, or a related field. Experience with programming languages like Python, R, or Java, and familiarity with machine learning frameworks such as TensorFlow or PyTorch, is often required. Additionally, experience in handling large datasets and deploying machine learning models in production environments is highly valued.

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