Salary for Mid-level / Intermediate QA Engineer in United States during 2024

Salary details

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

In the United States, the salary composition for a Mid-level/Intermediate QA Engineer in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. 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 success and individual performance, often ranging from 5% to 20% of the base salary. Additional remuneration, such as stock options, is more common in tech companies, especially startups or large tech firms, and can be a significant part of the compensation in regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of stock options but may provide other benefits like health insurance, retirement plans, and more.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in AI/ML and data science. Specializing in emerging technologies or tools can make you more valuable.
• Advanced Education: Pursuing a master's degree or relevant certifications can enhance your qualifications and open up higher-paying opportunities.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities and trends.
• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher pay.
• Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if the new company values your specific skill set more.

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. Some positions may prefer or require a master's degree, especially in more competitive markets or for roles with a strong emphasis on data science and machine learning. A solid understanding of software development and testing principles is essential, and coursework in AI/ML can be particularly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Software Quality Analyst (CSQA)
• ISTQB Certified Tester
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate

These certifications can help validate your skills and knowledge, making you a more attractive candidate for higher-paying roles.

Required Experience

Typically, a mid-level QA Engineer in AI/ML/Data Science is expected to have 3-5 years of experience in software quality assurance or a related field. Experience with AI/ML projects, data analysis, and familiarity with testing frameworks and tools specific to data science applications is highly desirable. Experience in agile development environments and a strong understanding of the software development lifecycle are also important.

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