Engineering Manager Salary in United States during 2024

Salary details

The average Engineering Manager salary lies between USD 200,000 and USD 314,400 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. 10, 2024

Top 20 Job Tags for Engineering Manager roles

The three most common job tag items assiciated with 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 | 968 jobs Machine Learning | 631 jobs Python | 585 jobs Computer Science | 474 jobs Architecture | 414 jobs Security | 334 jobs Pipelines | 322 jobs AWS | 315 jobs Java | 265 jobs SQL | 254 jobs Agile | 251 jobs Research | 236 jobs Testing | 225 jobs GCP | 203 jobs Azure | 196 jobs Privacy | 196 jobs Data pipelines | 190 jobs Spark | 181 jobs ML models | 165 jobs Distributed Systems | 163 jobs

Top 20 Job Perks/Benefits for Engineering Manager roles

The three most common job benefits and perks assiciated with Engineering Manager job listings are Career development, Health care and Equity / stock options. 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 | 803 jobs Health care | 437 jobs Equity / stock options | 354 jobs Startup environment | 329 jobs Flex hours | 292 jobs Salary bonus | 274 jobs Flex vacation | 228 jobs Parental leave | 222 jobs Competitive pay | 218 jobs Medical leave | 201 jobs Team events | 194 jobs Insurance | 171 jobs 401(k) matching | 110 jobs Wellness | 100 jobs Home office stipend | 86 jobs Unlimited paid time off | 66 jobs Transparency | 54 jobs Relocation support | 51 jobs Gear | 50 jobs Conferences | 41 jobs

Salary Composition

In the United States, the salary composition for an Engineering Manager in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10% to 20%. Additional remuneration, such as stock options or equity, can vary significantly depending on the company 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 provide smaller equity components.

Increasing Salary

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

• Skill Enhancement: Continuously update your technical and managerial skills. Specializing in emerging AI/ML technologies or methodologies can make you more valuable.
• Networking: Build a strong professional network within the AI/ML community. This can open up opportunities for higher-paying roles or consulting gigs.
• Leadership Roles: Aim for higher leadership positions such as Director of Engineering or VP of Engineering, which typically come with higher compensation.
• Industry Transition: Consider moving to industries that pay higher salaries for AI/ML expertise, such as finance or healthcare.
• Negotiation: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Engineering Manager roles 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 in leading tech companies or research-focused organizations. Advanced degrees can provide a deeper understanding of complex AI/ML concepts and demonstrate a commitment to the field.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate expertise. Some valuable certifications include:

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

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.

Required Experience

Typically, an Engineering Manager in AI/ML/Data Science is expected to have 8-12 years of experience in the field. This includes hands-on experience with AI/ML technologies, as well as several years in a leadership or managerial role. Experience in leading cross-functional teams, managing projects, and delivering AI/ML solutions is crucial. Additionally, experience in a specific industry can be beneficial, as it provides domain knowledge that can be applied to AI/ML projects.

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