Machine Learning Quality Engineer Salary in 2024

Salary details

The average Machine Learning Quality Engineer salary lies between USD 123,300 and USD 209,700 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. 15, 2024

Top 20 Job Tags for Machine Learning Quality Engineer roles

The three most common job tag items assiciated with Machine Learning Quality Engineer job listings are Machine Learning, Testing and Java. 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:

Machine Learning | 19 jobs Testing | 19 jobs Java | 18 jobs Engineering | 16 jobs Python | 15 jobs ML models | 13 jobs Selenium | 10 jobs Agile | 8 jobs Computer Science | 7 jobs Open Source | 6 jobs JavaScript | 4 jobs Git | 4 jobs Maven | 4 jobs SDLC | 4 jobs Generative AI | 4 jobs Scrum | 3 jobs Research | 2 jobs PhD | 2 jobs OOP | 2 jobs Kubernetes | 1 jobs

Top 20 Job Perks/Benefits for Machine Learning Quality Engineer roles

The three most common job benefits and perks assiciated with Machine Learning Quality Engineer job listings are Flex hours, 401(k) matching 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:

Flex hours | 18 jobs 401(k) matching | 10 jobs Equity / stock options | 10 jobs Health care | 10 jobs Competitive pay | 10 jobs Career development | 4 jobs

Salary Composition for a Machine Learning Quality Engineer

The salary for a Machine Learning Quality Engineer typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech hubs like Silicon Valley, bonuses might be more substantial compared to other regions. Additional remuneration can include stock options, especially in startups or large tech companies, and benefits like health insurance, retirement plans, and paid time off. The composition can also vary by industry, with tech and finance sectors often offering higher total compensation packages compared to other industries. Company size can influence the package as well, with larger companies potentially offering more comprehensive benefits and bonuses.

Steps to Increase Salary from This Position

To increase your salary from the position of a Machine Learning Quality Engineer, consider the following strategies:

• Skill Enhancement: Continuously update and expand your skill set, particularly in emerging AI/ML technologies and tools. Specializing in niche areas can make you more valuable.
• Advanced Education: Pursuing further education, such as a master's or Ph.D. in a related field, can open up higher-paying opportunities.
• Leadership Roles: Aim for leadership or managerial positions within your team or organization, which typically come with higher salaries.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Certifications: Obtain relevant certifications that can validate your expertise and potentially lead to salary increases.

Educational Requirements

Most Machine Learning Quality Engineer positions require at least a bachelor's degree in computer science, data science, engineering, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for more advanced roles. A strong foundation in mathematics, statistics, and programming is essential, as these are critical components of machine learning and data science.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials 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) Senior Data Scientist

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.

Required Experience

Typically, employers look for candidates with at least 3-5 years of experience in machine learning, data science, or a related field. Experience in quality assurance or software testing can also be beneficial. Practical experience with machine learning frameworks, data analysis, and model validation is crucial. Additionally, experience in a specific industry, such as finance, healthcare, or technology, can be advantageous depending on the employer's focus.

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