Machine Learning Quality Engineer Salary in United States during 2024

Salary details

The average Machine Learning Quality Engineer salary lies between USD 123,300 and USD 209,700 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: Nov. 17, 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 | 16 jobs Testing | 16 jobs Java | 15 jobs Python | 13 jobs Engineering | 13 jobs ML models | 11 jobs Selenium | 9 jobs Agile | 6 jobs Computer Science | 6 jobs Open Source | 5 jobs JavaScript | 4 jobs Git | 4 jobs Maven | 4 jobs SDLC | 4 jobs Generative AI | 4 jobs Scrum | 3 jobs PhD | 2 jobs OOP | 2 jobs Kubernetes | 1 jobs Research | 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 | 16 jobs 401(k) matching | 8 jobs Equity / stock options | 8 jobs Health care | 8 jobs Competitive pay | 8 jobs Career development | 3 jobs

Salary Composition

The salary for a Machine Learning Quality Engineer in the United States typically comprises a base salary, performance 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. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies, which can be a significant part of the compensation in startups or large tech firms. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and stock options, while other regions might offer more balanced packages. Industry and company size also play a role; larger companies or those in high-demand sectors like finance or healthcare might offer more competitive packages.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in niche areas like deep learning or natural language processing can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in a related field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into managerial or lead roles can significantly increase your salary.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Certifications: Obtaining advanced certifications can demonstrate your expertise and commitment to the field, potentially leading 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 senior roles. A strong foundation in mathematics, statistics, and programming is essential, as these are critical skills for developing and evaluating machine learning models.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

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

These certifications can provide a competitive edge by validating your skills and knowledge in specific platforms or methodologies.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in machine learning, data science, or a related field. Experience in quality assurance or software testing, particularly in AI/ML projects, is highly valued. Practical experience with machine learning frameworks, data analysis, and model evaluation is crucial. Additionally, experience in cross-functional teams and projects can be beneficial, as it demonstrates your ability to collaborate and communicate effectively.

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