DevOps Engineer Salary in United States during 2024

Salary details

The average DevOps Engineer salary lies between USD 107,957 and USD 183,300 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 DevOps Engineer roles

The three most common job tag items assiciated with DevOps Engineer job listings are DevOps, Python and Kubernetes. 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:

DevOps | 570 jobs Python | 518 jobs Kubernetes | 418 jobs AWS | 408 jobs Engineering | 407 jobs CI/CD | 399 jobs Security | 368 jobs Pipelines | 352 jobs Terraform | 345 jobs Docker | 313 jobs Machine Learning | 311 jobs Linux | 269 jobs Azure | 260 jobs Computer Science | 248 jobs Ansible | 243 jobs Jenkins | 229 jobs Architecture | 217 jobs GCP | 195 jobs Agile | 189 jobs Git | 180 jobs

Top 20 Job Perks/Benefits for DevOps Engineer roles

The three most common job benefits and perks assiciated with DevOps Engineer job listings are Career development, Flex hours and Health care. 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 | 399 jobs Flex hours | 204 jobs Health care | 183 jobs Startup environment | 159 jobs Team events | 125 jobs Competitive pay | 118 jobs Equity / stock options | 110 jobs Flex vacation | 101 jobs Salary bonus | 67 jobs Medical leave | 64 jobs Insurance | 64 jobs Parental leave | 41 jobs Gear | 36 jobs 401(k) matching | 33 jobs Wellness | 32 jobs Home office stipend | 24 jobs Conferences | 18 jobs Flexible spending account | 18 jobs Transparency | 17 jobs Pet friendly | 17 jobs

Salary Composition

In the United States, the salary composition for a DevOps Engineer specializing in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In tech hubs like Silicon Valley, New York, or Seattle, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: Performance-based bonuses are common and can range from 10% to 20% of the base salary. These are often tied to individual performance, team success, or company profitability.

• Additional Remuneration: This can include stock options, especially in startups or tech companies, as well as benefits like health insurance, retirement contributions, and paid time off. Larger companies might offer more comprehensive benefits packages.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in AI/ML and DevOps. Specializing in emerging technologies or tools can make you more valuable.

• Advanced Education: Pursuing a master's degree or specialized certifications can enhance your qualifications and open up higher-paying opportunities.

• Networking: Engage with professional networks and communities. This can lead to opportunities in higher-paying companies or roles.

• Leadership Roles: Aim for leadership or managerial positions, which typically offer higher salaries.

• Industry Shift: Consider moving to industries that pay more for AI/ML expertise, such as finance, healthcare, or tech giants.

Educational Requirements

Most positions in this field require at least a bachelor's degree in computer science, engineering, or a related field. However, a master's degree or Ph.D. in data science, machine learning, or a related discipline can be advantageous and sometimes necessary for more advanced roles.

Helpful Certifications

Certifications can bolster your credentials and demonstrate expertise. Some valuable certifications include:

• AWS Certified DevOps Engineer: Demonstrates proficiency in deploying, managing, and operating applications on AWS.

• Google Professional Data Engineer: Validates your ability to design, build, and manage data processing systems.

• Certified Kubernetes Administrator (CKA): Useful for managing containerized applications, which is often a part of DevOps roles.

• TensorFlow Developer Certificate: Shows proficiency in using TensorFlow for machine learning tasks.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in DevOps, with a focus on AI/ML projects. Experience with cloud platforms, CI/CD pipelines, and infrastructure as code is often required. Familiarity with data science tools and frameworks is also beneficial.

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