Salary for Executive-level / Director Machine Learning Engineer during 2024

Salary details

The average executive-level / director Machine Learning Engineer salary lies between USD 175,100 and USD 244,900 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

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 2024 and the number of open jobs that where associated with them during that period:

Machine Learning | 45 jobs Engineering | 43 jobs Python | 31 jobs ML models | 26 jobs Architecture | 25 jobs Computer Science | 25 jobs PyTorch | 21 jobs LLMs | 21 jobs Research | 19 jobs AWS | 18 jobs Pipelines | 18 jobs Statistics | 16 jobs Deep Learning | 15 jobs TensorFlow | 15 jobs Scikit-learn | 15 jobs PhD | 15 jobs Testing | 13 jobs Java | 12 jobs NLP | 11 jobs RAG | 11 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 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 | 45 jobs Health care | 29 jobs Startup environment | 29 jobs Equity / stock options | 20 jobs Competitive pay | 19 jobs Flex hours | 17 jobs Salary bonus | 16 jobs 401(k) matching | 14 jobs Parental leave | 13 jobs Wellness | 13 jobs Insurance | 13 jobs Flex vacation | 10 jobs Home office stipend | 9 jobs Team events | 5 jobs Medical leave | 4 jobs Relocation support | 1 jobs Pet friendly | 1 jobs Flexible spending account | 1 jobs Unlimited paid time off | 1 jobs Paid sabbatical | 1 jobs

Salary Composition

The salary for an Executive-level or Director Machine Learning Engineer typically comprises several components: a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity. The composition can vary significantly depending on the region, industry, and company size.

• Region: In tech hubs like Silicon Valley, New York, or Seattle, the base salary might be higher due to the cost of living and competition for talent. In contrast, regions with a lower cost of living might offer a smaller base salary but compensate with other benefits.
• Industry: Industries such as finance, healthcare, and technology often offer higher salaries due to the critical nature of AI/ML applications in these fields.
• Company Size: Larger companies may offer more comprehensive compensation packages, including significant bonuses and stock options, while startups might offer lower base salaries but more equity.

Increasing Salary Further

To increase your salary from this position, 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, reinforcement learning, or AI ethics can make you more valuable.
• Leadership and Management Skills: Enhance your leadership capabilities by taking on more responsibilities, leading larger teams, or managing cross-functional projects.
• Networking and Industry Presence: Build a strong professional network and establish yourself as a thought leader by speaking at conferences, publishing papers, or contributing to open-source projects.
• Transition to Higher Roles: Aim for roles such as Chief Data Officer (CDO) or Chief Technology Officer (CTO), which typically come with higher compensation.

Educational Requirements

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. Additionally, an MBA or a degree in management can be beneficial for roles that involve significant leadership responsibilities.

Helpful Certifications

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

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

These certifications can help validate your skills and knowledge in specific platforms or methodologies.

Required Experience

Typically, a Director of Machine Learning would have 10+ years of experience in the field, with a strong track record of leading successful AI/ML projects. Experience in managing teams, developing AI strategies, and implementing machine learning solutions at scale is crucial. Prior experience in a managerial or leadership role is often required.

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