Salary for Senior-level / Expert Machine Learning Quality Engineer during 2024

Salary details

The average senior-level / expert 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. 22, 2024

Top 20 Job Tags for Senior-level / Expert Machine Learning Quality Engineer roles

The three most common job tag items assiciated with senior-level / expert 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 | 13 jobs Testing | 13 jobs Java | 12 jobs Python | 10 jobs Engineering | 10 jobs ML models | 8 jobs Selenium | 5 jobs JavaScript | 4 jobs Git | 4 jobs Maven | 4 jobs SDLC | 4 jobs Generative AI | 4 jobs Scrum | 3 jobs Agile | 3 jobs Research | 2 jobs PhD | 2 jobs Computer Science | 2 jobs OOP | 2 jobs Open Source | 1 jobs Kubernetes | 1 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Machine Learning Quality Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 | 12 jobs 401(k) matching | 6 jobs Equity / stock options | 6 jobs Health care | 6 jobs Competitive pay | 6 jobs Career development | 2 jobs

Salary Composition

The salary for a Senior-level or Expert Machine Learning Quality Engineer typically comprises several components: a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The composition can vary significantly depending on the region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but companies often offer substantial stock options as part of the compensation package. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with higher bonuses or other benefits. Industries such as finance or healthcare might offer higher bonuses due to the critical nature of the work, while startups might offer more equity to attract talent.

Increasing Salary

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

• Specialization: Develop expertise in a niche area of machine learning or data science that is in high demand, such as deep learning, natural language processing, or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as a Machine Learning Team Lead or Director of AI, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or a Ph.D. can also enhance your qualifications.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends in the industry.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most senior-level positions in machine learning and data science require at least a master's degree in a related field such as computer science, data science, statistics, or mathematics. A Ph.D. is often preferred, especially for roles that involve research or the development of new algorithms. Strong foundational knowledge in programming, data structures, and algorithms is essential, along with expertise in machine learning frameworks and tools.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. 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 validate your skills and knowledge, making you a more attractive candidate to potential employers.

Required Experience

Typically, a Senior-level Machine Learning Quality Engineer is expected to have at least 5-10 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and quality assurance processes. Experience in leading projects, mentoring junior engineers, and collaborating with cross-functional teams is also highly valued. A proven track record of successful projects and contributions to the field can significantly bolster your candidacy.

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