Salary for Executive-level / Director Head of Machine Learning during 2024
💰 The median Salary for Executive-level / Director Head of Machine Learning during 2024 is USD 336,500
✏️ This salary info is based on 6 individual salaries reported during 2024
Salary details
The average executive-level / director Head of Machine Learning salary lies between USD 245,000 and USD 438,000 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.
- Job title
- Head of Machine Learning
- Experience
- Executive-level / Director
- Region
- global/worldwide
- Salary year
- 2024
- Sample size
- 6
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated: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 jobsTop 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 jobsSalary Composition for Executive-Level AI/ML Roles
The salary for an executive-level or director head of machine learning position typically comprises a mix of base salary, bonuses, and additional remuneration such as stock options or equity. The composition can vary significantly depending on the region, industry, and company size.
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Base Salary: This is the fixed component and usually forms the largest part of the total compensation package. In tech hubs like Silicon Valley, New York, or London, the base salary might be higher due to the cost of living and competitive market rates.
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Bonuses: Performance-based bonuses are common and can be a significant part of the compensation. These are often tied to individual, team, or company performance metrics and can vary from 10% to 50% of the base salary.
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Equity/Stock Options: Especially in startups or tech companies, equity can be a substantial part of the compensation package. This aligns the executive's interests with the company's long-term success and can be highly lucrative if the company performs well.
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Other Benefits: Additional benefits might include health insurance, retirement plans, and other perks like relocation assistance, professional development funds, or company cars.
Steps to Increase Salary from This Position
To increase your salary further from an executive-level position, consider the following strategies:
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Expand Your Role: Take on additional responsibilities or oversee larger teams or projects. Demonstrating your ability to drive significant business impact can justify a salary increase.
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Pursue Further Education: Advanced degrees or executive education programs can enhance your credentials and open up higher-paying opportunities.
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Network and Build Influence: Establish yourself as a thought leader in the AI/ML community. Speaking at conferences, publishing papers, or contributing to industry discussions can increase your visibility and value.
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Negotiate Equity: If you're in a startup or tech company, negotiating for more equity can be a way to increase your overall compensation, especially if the company is poised for growth.
Educational Requirements for Executive-Level AI/ML Roles
Most executive-level positions 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. can be advantageous, especially for roles that require deep technical expertise or research experience. Business acumen is also important, so an MBA or similar qualification can be beneficial for roles that involve strategic decision-making and leadership.
Helpful Certifications
While not always mandatory, certain certifications can enhance your profile:
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Certified Analytics Professional (CAP): This certification demonstrates your ability to transform data into valuable insights.
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AWS Certified Machine Learning – Specialty: Useful if you're working with AWS technologies, this certification validates your expertise in building, training, and deploying machine learning models on AWS.
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Google Professional Machine Learning Engineer: This certification is beneficial if you're working within the Google Cloud ecosystem.
Experience Requirements
Typically, candidates for executive-level AI/ML roles have extensive experience, often 10-15 years, in data science, machine learning, or related fields. This experience should include:
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Leadership Experience: Proven track record of leading teams and managing large-scale projects.
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Technical Expertise: Deep understanding of machine learning algorithms, data processing, and model deployment.
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Strategic Vision: Ability to align AI/ML initiatives with business goals and drive innovation.
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