Salary for Executive-level / Director AI Engineer during 2024

Salary details

The average executive-level / director AI Engineer salary lies between USD 150,000 and USD 218,860 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 Executive-level / Director AI Engineer roles

The three most common job tag items assiciated with executive-level / director AI Engineer job listings are Engineering, Machine Learning and Computer Science. 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:

Engineering | 20 jobs Machine Learning | 18 jobs Computer Science | 16 jobs Python | 13 jobs Generative AI | 12 jobs Research | 11 jobs LLMs | 10 jobs NLP | 9 jobs Architecture | 9 jobs Agile | 9 jobs Deep Learning | 8 jobs Testing | 8 jobs Pipelines | 8 jobs Azure | 7 jobs Java | 7 jobs Finance | 6 jobs GCP | 6 jobs Model training | 6 jobs APIs | 6 jobs AWS | 5 jobs

Top 20 Job Perks/Benefits for Executive-level / Director AI Engineer roles

The three most common job benefits and perks assiciated with executive-level / director AI Engineer job listings are Career development, Flex hours and Competitive pay. 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 | 18 jobs Flex hours | 12 jobs Competitive pay | 10 jobs Health care | 9 jobs Flex vacation | 8 jobs Startup environment | 8 jobs Salary bonus | 8 jobs Equity / stock options | 7 jobs Insurance | 5 jobs Conferences | 4 jobs Medical leave | 4 jobs Wellness | 3 jobs Team events | 3 jobs Home office stipend | 3 jobs 401(k) matching | 2 jobs Parental leave | 2 jobs Signing bonus | 2 jobs Unlimited paid time off | 2 jobs Fertility benefits | 2 jobs Gear | 1 jobs

Salary Composition for Executive-Level AI/ML/Data Science Roles

The salary for an executive-level AI/ML/Data Science position typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly based on region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, regions with a lower cost of living might offer a smaller base salary but compensate with substantial bonuses or equity. Industries such as finance or healthcare might offer higher bonuses due to the critical nature of AI applications in these fields. Larger companies often provide more comprehensive compensation packages, including benefits like health insurance, retirement plans, and professional development allowances.

Steps to Increase Salary from an Executive-Level Position

To increase your salary from an executive-level position, consider the following strategies:

• Expand Your Network: Building relationships with other leaders in the industry can open doors to new opportunities and insights into higher-paying roles.
• Enhance Your Skills: Stay updated with the latest AI/ML technologies and methodologies. Consider learning about emerging fields like quantum computing or advanced neural networks.
• Seek Leadership Roles: Taking on more significant leadership responsibilities or moving to a larger organization can lead to salary increases.
• Negotiate Effectively: When discussing compensation, highlight your achievements and the value you bring to the organization.
• Explore Consulting Opportunities: Offering your expertise as a consultant can supplement your income and increase your market value.

Educational Requirements for Executive-Level AI/ML/Data Science Roles

Most executive-level positions in AI/ML/Data Science require at least a master's degree in a relevant field such as computer science, data science, or engineering. A Ph.D. is often preferred, especially for roles that involve leading research and development teams. Additionally, an MBA can be beneficial for those looking to move into roles that require a strong understanding of business strategy and management.

Helpful Certifications for AI/ML/Data Science Executives

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

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can help you stay competitive and showcase your expertise in specific tools and platforms.

Experience Required for Executive-Level AI/ML/Data Science Roles

Typically, these roles require extensive experience, often 10-15 years, in AI/ML or related fields. This experience should include a mix of technical expertise, project management, and leadership roles. Experience in leading cross-functional teams, managing large-scale projects, and a proven track record of successful AI/ML implementations are crucial. Additionally, experience in a specific industry can be advantageous, as it provides context and understanding of industry-specific challenges and opportunities.

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