Salary for Senior-level / Expert Engineering Manager in United States during 2024

Salary details

The average senior-level / expert Engineering Manager salary lies between USD 189,000 and USD 294,000 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 Senior-level / Expert Engineering Manager roles

The three most common job tag items assiciated with senior-level / expert Engineering Manager job listings are Engineering, Machine Learning 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:

Engineering | 369 jobs Machine Learning | 256 jobs Python | 238 jobs Computer Science | 223 jobs Architecture | 187 jobs Security | 182 jobs Java | 148 jobs AWS | 124 jobs Pipelines | 123 jobs SQL | 107 jobs Agile | 104 jobs GCP | 101 jobs Testing | 97 jobs Azure | 90 jobs Data pipelines | 80 jobs JavaScript | 79 jobs NLP | 76 jobs Spark | 75 jobs Generative AI | 75 jobs Research | 73 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Engineering Manager roles

The three most common job benefits and perks assiciated with senior-level / expert Engineering Manager 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 | 302 jobs Health care | 141 jobs Startup environment | 127 jobs Equity / stock options | 123 jobs Medical leave | 100 jobs Salary bonus | 96 jobs Flex hours | 94 jobs Competitive pay | 88 jobs Flex vacation | 76 jobs Parental leave | 63 jobs Team events | 53 jobs Insurance | 49 jobs Wellness | 48 jobs 401(k) matching | 31 jobs Unlimited paid time off | 22 jobs Relocation support | 19 jobs Transparency | 16 jobs Home office stipend | 16 jobs Fertility benefits | 13 jobs Conferences | 12 jobs

Salary Composition

In the United States, the salary for a Senior-level or Expert Engineering Manager in AI/ML/Data Science typically comprises several components. The fixed base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually account for 10% to 20%. Additional remuneration may include stock options, restricted stock units (RSUs), or other equity incentives, which can vary significantly depending on the company's size and industry. For instance, tech giants and startups in Silicon Valley might offer substantial equity packages, while companies in other regions or industries might focus more on cash bonuses. Benefits such as health insurance, retirement plans, and other perks also contribute to the overall compensation but are not typically included in the salary index figures.

Increasing Salary Further

To increase your salary beyond the median of USD 236,000, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or AI ethics, which are in high demand.
• Pursue Leadership Roles: Aim for roles with greater responsibility, such as Director of AI/ML or VP of Data Science, which typically offer higher compensation.
• Negotiate Equity: If you're with a startup or a tech company, negotiate for more equity, which can significantly increase your total compensation if the company performs well.
• Consulting or Advisory Roles: Take on consulting or advisory roles in addition to your full-time job, which can provide additional income and broaden your professional network.

Educational Requirements

Most Senior-level or Expert Engineering Manager positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Data Science, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and strategic decision-making. Advanced degrees can provide a deeper understanding of AI/ML algorithms, data analysis, and business acumen, which are crucial for leadership roles.

Helpful Certifications

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

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your technical skills and knowledge of specific platforms or tools, making you a more attractive candidate for senior roles.

Required Experience

Typically, candidates for a Senior-level or Expert Engineering Manager position in AI/ML/Data Science are expected to have at least 8-10 years of experience in the field. This experience should include a mix of technical expertise in AI/ML, project management, and leadership roles. Experience in managing cross-functional teams, overseeing large-scale projects, and driving strategic initiatives is highly valued. Additionally, a proven track record of successful AI/ML implementations and the ability to translate business needs into technical solutions are crucial.

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