Salary for Mid-level / Intermediate QA Engineer during 2024

Salary details

The average mid-level / intermediate QA Engineer salary lies between USD 92,000 and USD 143,750 globally. 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.

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 Mid-level / Intermediate QA Engineer roles

The three most common job tag items assiciated with mid-level / intermediate QA Engineer job listings are Python, Testing 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:

Python | 45 jobs Testing | 45 jobs Engineering | 38 jobs Machine Learning | 27 jobs Computer Science | 27 jobs Agile | 23 jobs Jira | 19 jobs APIs | 19 jobs SQL | 17 jobs Pipelines | 14 jobs CI/CD | 14 jobs LLMs | 13 jobs Selenium | 12 jobs Security | 11 jobs Java | 11 jobs JavaScript | 10 jobs Linux | 9 jobs Scrum | 9 jobs GitLab | 8 jobs ML models | 8 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate QA 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 | 35 jobs Health care | 21 jobs Equity / stock options | 14 jobs Flex hours | 13 jobs Medical leave | 11 jobs Startup environment | 9 jobs Competitive pay | 9 jobs Parental leave | 8 jobs Insurance | 8 jobs Salary bonus | 8 jobs Flex vacation | 7 jobs Team events | 5 jobs Relocation support | 5 jobs Flexible spending account | 5 jobs Wellness | 4 jobs Gear | 4 jobs Travel | 3 jobs Home office stipend | 3 jobs Unlimited paid time off | 3 jobs 401(k) matching | 2 jobs

Salary Composition

The salary for a Mid-level/Intermediate QA Engineer in AI/ML/Data Science typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or benefits. The fixed base salary is the largest component, often accounting for 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and individual performance, usually ranging from 10-20%. Additional remuneration, such as stock options, profit-sharing, or benefits like health insurance and retirement plans, can make up the remaining 5-10%.

Regional differences play a significant role in salary composition. For instance, tech hubs like San Francisco or New York may offer higher base salaries and stock options due to the high cost of living and competitive job market. In contrast, companies in smaller cities might offer lower base salaries but compensate with other benefits. Industry and company size also influence salary composition; larger tech companies or those in high-demand sectors like finance or healthcare may offer more lucrative packages compared to smaller startups.

Steps to Increase Salary

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

• Skill Enhancement: Continuously upgrade your technical skills, especially in emerging AI/ML technologies, to stay relevant and valuable.
• Advanced Education: Pursuing a master's degree or specialized courses in AI/ML can make you more competitive.
• Leadership Roles: Seek opportunities to lead projects or teams, which can position you for promotions and salary increases.
• Networking: Build a strong professional network to learn about higher-paying opportunities and industry trends.
• Certifications: Obtain relevant certifications that can validate your expertise and potentially lead to higher-paying roles.

Educational Requirements

Most mid-level QA Engineer positions in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. A strong foundation in programming, data structures, and algorithms is essential. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning model validation.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your commitment to the field. Some valuable certifications include:

• ISTQB Certified Tester: A widely recognized certification for software testers.
• Certified Software Quality Analyst (CSQA): Focuses on quality assurance principles and practices.
• AWS Certified Machine Learning – Specialty: Validates expertise in building, training, and deploying machine learning models on AWS.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing and implementing ML models on Google Cloud.

Required Experience

Typically, a mid-level QA Engineer in AI/ML/Data Science should have 3-5 years of experience in software testing or quality assurance. Experience with testing frameworks, automation tools, and familiarity with AI/ML concepts is often required. Hands-on experience with data analysis, model validation, and performance testing in AI/ML projects is highly beneficial.

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