Salary for Executive-level / Director Head of Machine Learning in United States during 2024

Salary details

The average executive-level / director Head of Machine Learning salary lies between USD 245,000 and USD 438,000 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. 17, 2024

Top 20 Job Tags for Executive-level / Director Head of Machine Learning roles

The three most common job tag items assiciated with executive-level / director Head of Machine Learning job listings are Machine Learning, Python 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:

Machine Learning | 17 jobs Python | 12 jobs Computer Science | 12 jobs R | 11 jobs ML models | 10 jobs Statistics | 10 jobs PhD | 7 jobs Big Data | 6 jobs Research | 6 jobs Data Mining | 6 jobs Engineering | 6 jobs Security | 6 jobs Architecture | 6 jobs Statistical modeling | 6 jobs R&D | 5 jobs Generative AI | 5 jobs NLP | 4 jobs GPU | 4 jobs Industrial | 4 jobs Pipelines | 4 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Head of Machine Learning roles

The three most common job benefits and perks assiciated with executive-level / director Head of Machine Learning job listings are Career development, Startup environment and Conferences. 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 | 16 jobs Startup environment | 7 jobs Conferences | 6 jobs Equity / stock options | 2 jobs Flex hours | 2 jobs Health care | 2 jobs 401(k) matching | 1 jobs Flex vacation | 1 jobs Transparency | 1 jobs Team events | 1 jobs Insurance | 1 jobs Salary bonus | 1 jobs Home office stipend | 1 jobs

Salary Composition for Executive-Level AI/ML Roles

In the United States, the salary for an executive-level or director head of machine learning typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity. The base salary often forms the largest portion, accounting for approximately 60-70% of the total compensation package. Performance bonuses can range from 15-25%, depending on the company's profitability and individual performance metrics. Additional remuneration, such as stock options or equity, can make up 10-20% of the total package, especially in tech companies or startups where equity is a significant incentive.

The composition can vary significantly based on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more substantial equity components due to the competitive market. In contrast, companies in the Midwest or South might offer lower base salaries but compensate with higher bonuses or other benefits. Larger companies often provide more structured and predictable compensation packages, while startups might offer lower base salaries but higher potential upside through equity.

Steps to Increase Salary from This Position

To increase your salary further from an executive-level position in AI/ML, consider the following strategies:

• Expand Your Network: Building relationships with industry leaders and influencers can open doors to higher-paying opportunities.
• 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: Aim for positions with broader responsibilities, such as Chief AI Officer or VP of Technology, which typically come with higher compensation.
• Negotiate Equity: If you're in a startup or tech company, negotiating for more equity can significantly increase your long-term earnings.
• Consulting and Speaking Engagements: Establish yourself as a thought leader in AI/ML by engaging in consulting or speaking at conferences, which can supplement your income.

Educational Requirements

Most executive-level roles in AI/ML 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 significant research and development responsibilities. Candidates with a strong academic background in machine learning, artificial intelligence, or related disciplines are highly sought after.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your expertise in AI/ML. Some valuable certifications include:

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

These certifications can help validate your skills and knowledge, making you a more attractive candidate for executive roles.

Experience Requirements

Typically, candidates for executive-level AI/ML roles are expected to have at least 10-15 years of experience in the field. This experience should include a mix of technical expertise, project management, and leadership roles. Experience in leading large teams, managing complex projects, and driving strategic initiatives is crucial. Additionally, a proven track record of successful AI/ML implementations and innovations is highly desirable.

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