QA Engineer Salary in United States during 2024

Salary details

The average QA Engineer salary lies between USD 92,000 and USD 150,000 in the United States. 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 QA Engineer roles

The three most common job tag items assiciated with QA Engineer job listings are Testing, 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:

Testing | 140 jobs Python | 131 jobs Engineering | 110 jobs Machine Learning | 78 jobs Agile | 72 jobs Computer Science | 65 jobs SQL | 58 jobs APIs | 56 jobs Java | 45 jobs Jira | 44 jobs CI/CD | 39 jobs AWS | 36 jobs Pipelines | 36 jobs Selenium | 34 jobs Architecture | 32 jobs Security | 30 jobs Scrum | 28 jobs ETL | 27 jobs JavaScript | 26 jobs Research | 26 jobs

Top 20 Job Perks/Benefits for QA Engineer roles

The three most common job benefits and perks assiciated with QA 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 | 108 jobs Health care | 68 jobs Flex hours | 56 jobs Equity / stock options | 48 jobs Competitive pay | 32 jobs Startup environment | 27 jobs Insurance | 27 jobs Medical leave | 26 jobs Flex vacation | 24 jobs Salary bonus | 23 jobs Parental leave | 17 jobs Relocation support | 14 jobs Team events | 11 jobs Home office stipend | 10 jobs Wellness | 9 jobs Gear | 9 jobs Transparency | 8 jobs Unlimited paid time off | 8 jobs 401(k) matching | 7 jobs Flexible spending account | 5 jobs

Salary Composition

In the United States, the salary composition for a QA Engineer specializing in AI/ML/Data Science can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. In tech hubs like Silicon Valley, New York, or Seattle, the base salary might be higher due to the cost of living and competitive job market. Bonuses are often performance-based and can range from 5% to 20% of the base salary, depending on the company's profitability and individual performance. Additional remuneration might include stock options, especially in startups or tech giants, and benefits such as health insurance, retirement plans, and professional development allowances.

Increasing Salary

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

• Skill Enhancement: Continuously upgrade your skills in AI/ML and data science. Mastering new tools and technologies can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized certifications can open up higher-paying roles.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities.
• Leadership Roles: Aim for leadership or managerial positions within your team or organization, which typically come with higher pay.
• Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if you are moving to a larger or more prestigious firm.

Educational Requirements

Most positions in AI/ML/Data Science for QA Engineers require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or Ph.D. can be advantageous and sometimes necessary for more advanced roles. Courses in machine learning, data analysis, and software engineering are particularly relevant.

Helpful Certifications

Certifications can bolster your credentials and demonstrate your expertise. Some valuable certifications include:

• Certified Machine Learning Specialist (CMLS)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate

These certifications can help you stand out in the job market and may lead to higher salary offers.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in software quality assurance, with a focus on AI/ML or data science projects. Experience with testing frameworks, automation tools, and familiarity with programming languages like Python or R is often required. Experience in a specific industry, such as finance or healthcare, can also be beneficial.

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