Salary for Executive-level / Director Engineer during 2024

Salary details

The average executive-level / director Engineer salary lies between USD 170,000 and USD 290,000 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.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 10, 2024

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

The three most common job tag items assiciated with executive-level / director Engineer job listings are Engineering, 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:

Engineering | 872 jobs Python | 594 jobs Computer Science | 508 jobs Machine Learning | 489 jobs Architecture | 484 jobs Security | 375 jobs AWS | 373 jobs Agile | 364 jobs SQL | 356 jobs Pipelines | 341 jobs Java | 308 jobs Testing | 294 jobs Big Data | 258 jobs ETL | 238 jobs Azure | 231 jobs Spark | 230 jobs Data pipelines | 220 jobs Research | 188 jobs Finance | 185 jobs Privacy | 180 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Engineer job listings are Career development, Health care and Startup environment. 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 | 759 jobs Health care | 382 jobs Startup environment | 297 jobs Equity / stock options | 243 jobs Flex hours | 224 jobs Competitive pay | 199 jobs Wellness | 198 jobs Salary bonus | 190 jobs Flex vacation | 179 jobs Insurance | 176 jobs Parental leave | 156 jobs Team events | 149 jobs Medical leave | 129 jobs 401(k) matching | 88 jobs Transparency | 33 jobs Conferences | 31 jobs Unlimited paid time off | 31 jobs Home office stipend | 27 jobs Relocation support | 20 jobs Fertility benefits | 17 jobs

Salary Composition

The salary for an executive-level or director engineer position in AI/ML/Data Science typically comprises several components. The fixed base salary is often the largest portion, providing a stable income. Bonuses are common and can be tied to individual performance, team performance, or company-wide success. These bonuses can be substantial, especially in larger companies or high-growth industries. Additional remuneration might include stock options or equity, particularly in tech startups or publicly traded companies, which can significantly increase total compensation. Benefits such as health insurance, retirement plans, and other perks also contribute to the overall package. The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York might offer higher base salaries and equity, while smaller companies might offer more in bonuses to attract top talent.

Next Steps for Salary Increase

To increase your salary further from this position, consider the following strategies:

• Expand Your Skill Set: Continuously update your technical skills and stay abreast of the latest trends in AI/ML. Specializing in emerging areas like deep learning, natural language processing, or AI ethics can make you more valuable.
• Leadership Development: Enhance your leadership and management skills. Taking on more significant responsibilities or leading larger teams can justify a higher salary.
• Networking: Build a strong professional network. Engaging with industry leaders and participating in conferences can open up new opportunities.
• Performance Metrics: Demonstrate your impact on the company’s bottom line. Quantifiable achievements can be a strong negotiating point for a raise.
• Consider Relocation: If feasible, relocating to a region with higher salary standards for your role can be beneficial.

Educational Requirements

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. can be advantageous, especially for roles that involve significant research components or are in academia. Business administration degrees (e.g., an MBA) can also be beneficial, particularly for roles that require a strong understanding of business strategy and operations.

Helpful Certifications

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

• 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 demonstrate a commitment to the field and a recognized level of expertise.

Required Experience

Typically, a minimum of 10-15 years of experience in the tech industry is expected, with at least 5 years in a leadership role. Experience should include hands-on work with AI/ML technologies, project management, and strategic planning. Experience in different industries can be a plus, as it brings diverse perspectives and problem-solving approaches.

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