Salary for Executive-level / Director Machine Learning Engineer in United States during 2023

Salary details

The average executive-level / director Machine Learning Engineer salary lies between USD 160,000 and USD 200,000 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: Dec. 15, 2024

Salary trend

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

The three most common job tag items assiciated with executive-level / director Machine Learning Engineer job listings are Machine Learning, Engineering and Python. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Machine Learning | 16 jobs Engineering | 16 jobs Python | 14 jobs Computer Science | 11 jobs Java | 10 jobs Testing | 8 jobs GCP | 8 jobs Google Cloud | 8 jobs Hadoop | 7 jobs SQL | 7 jobs ML models | 7 jobs R | 6 jobs Spark | 6 jobs Research | 6 jobs Security | 6 jobs Architecture | 6 jobs Agile | 6 jobs TensorFlow | 5 jobs Keras | 5 jobs PyTorch | 5 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Machine Learning Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 14 jobs Health care | 6 jobs Flex hours | 5 jobs Startup environment | 5 jobs Insurance | 5 jobs Equity / stock options | 4 jobs Flex vacation | 4 jobs Wellness | 4 jobs Salary bonus | 3 jobs Lunch / meals | 2 jobs Competitive pay | 2 jobs Medical leave | 2 jobs 401(k) matching | 1 jobs Parental leave | 1 jobs Gear | 1 jobs Team events | 1 jobs Flexible spending account | 1 jobs Fertility benefits | 1 jobs

Salary Composition

In the United States, the salary for an Executive-level or Director Machine Learning Engineer typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Performance bonuses can vary significantly, often between 10% to 20%, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, can be a significant part of the package, particularly in startups or large tech firms, and may account for 10% to 30% of the total compensation. The composition can vary by region, with tech hubs like Silicon Valley offering higher equity components, while regions with a lower cost of living might offer a higher base salary. Industry also plays a role; for instance, finance and healthcare sectors might offer higher bonuses compared to traditional tech companies.

Increasing Salary Further

To increase your salary from an Executive-level or Director position, consider the following strategies:

• Expand Your Skill Set: Acquiring new skills in emerging areas like AI ethics, quantum computing, or advanced data analytics can make you more valuable.
• Pursue Leadership Roles: Transitioning into a VP or C-level position can significantly increase your earning potential.
• Negotiate Equity: In startups or tech companies, negotiating for more equity can be lucrative if the company performs well.
• Industry Shift: Moving to a higher-paying industry, such as finance or pharmaceuticals, can result in a salary increase.
• Consulting or Advisory Roles: Taking on consulting roles or board memberships can supplement your income.

Educational Requirements

Most Executive-level or Director Machine Learning Engineer positions require at least a master's degree in a relevant field such as Computer Science, Data Science, or Electrical Engineering. A Ph.D. is often preferred, especially for roles that involve significant research and development responsibilities. Additionally, a strong foundation in mathematics, statistics, and computer programming is essential. Some roles may also value an MBA or other management-related qualifications, particularly if the position involves significant leadership and strategic responsibilities.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile:

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

These certifications demonstrate expertise in specific tools and platforms, which can be advantageous in technical interviews and negotiations.

Required Experience

Typically, a minimum of 10-15 years of experience in the field of machine learning, data science, or a related area is required for an Executive-level or Director position. This experience should include:

• Leading teams and projects in AI/ML.
• Proven track record of deploying machine learning models in production.
• Experience in strategic planning and execution.
• Strong understanding of industry trends and emerging technologies.

Experience in a managerial or leadership role is crucial, as these positions often require overseeing large teams and projects.

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