Salary for Executive-level / Director AI Engineer in United States during 2024

Salary details

The average executive-level / director AI Engineer salary lies between USD 150,000 and USD 225,000 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. 24, 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 | 19 jobs Machine Learning | 17 jobs Computer Science | 15 jobs Python | 13 jobs Research | 11 jobs Generative AI | 11 jobs NLP | 9 jobs Architecture | 9 jobs Agile | 9 jobs LLMs | 9 jobs Deep Learning | 8 jobs Testing | 8 jobs Pipelines | 8 jobs Azure | 7 jobs Java | 7 jobs Finance | 6 jobs Model training | 6 jobs APIs | 6 jobs AWS | 5 jobs GCP | 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 | 17 jobs Flex hours | 11 jobs Competitive pay | 9 jobs Health care | 8 jobs Flex vacation | 7 jobs Startup environment | 7 jobs Salary bonus | 7 jobs Equity / stock options | 6 jobs Insurance | 5 jobs Conferences | 4 jobs Wellness | 3 jobs Team events | 3 jobs Medical leave | 3 jobs Home office stipend | 3 jobs 401(k) matching | 2 jobs Signing bonus | 2 jobs Unlimited paid time off | 2 jobs Fertility benefits | 2 jobs Parental leave | 1 jobs Gear | 1 jobs

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

In the United States, the salary for an Executive-level or Director AI Engineer typically comprises several components. The fixed base salary often forms the largest portion, accounting for approximately 60-70% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up about 15-25%. Additional remuneration may include stock options, equity, or other long-term incentives, which can vary significantly depending on the company size, industry, and region. For instance, tech giants in Silicon Valley might offer substantial equity packages, while companies in other regions might focus more on cash bonuses. Benefits such as health insurance, retirement plans, and other perks also contribute to the overall compensation.

Steps to Increase Salary from This Position

To increase your salary beyond the median of USD 187,550, consider the following strategies:

• Expand Your Skill Set: Stay updated with the latest AI/ML technologies and methodologies. Specializing in emerging areas like deep learning, natural language processing, or AI ethics can make you more valuable.
• Pursue Leadership Opportunities: Taking on more significant leadership roles or managing larger teams can justify a higher salary.
• Network and Build Industry Connections: Engaging with industry leaders and participating in conferences can open doors to higher-paying opportunities.
• Negotiate Effectively: When discussing salary, highlight your achievements, the value you bring to the company, and market salary data to support your case.
• Consider Relocation: Some regions, particularly tech hubs like San Francisco or New York, may offer higher salaries due to the cost of living and demand for talent.

Educational Requirements

For an Executive-level AI/ML/Data Science position, a strong educational background is crucial. Most candidates hold at least a master's degree in computer science, data science, machine learning, or a related field. A Ph.D. can be advantageous, especially for roles that require deep technical expertise or involve research and development. Additionally, a solid foundation in mathematics, statistics, and programming is essential.

Helpful Certifications

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

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

These certifications can validate your skills and knowledge, making you a more competitive candidate.

Experience Requirements

Typically, candidates for this role have at least 10-15 years of experience in the field, with a significant portion in leadership or managerial positions. Experience in developing and deploying AI/ML models, leading data science teams, and working on large-scale projects is often required. A proven track record of driving business value through AI initiatives is also highly valued.

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