DevOps Engineer Salary in 2024

Salary details

The average DevOps Engineer salary lies between USD 100,000 and USD 180,000 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. 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 | 563 jobs Python | 512 jobs Kubernetes | 413 jobs Engineering | 405 jobs AWS | 404 jobs CI/CD | 396 jobs Security | 363 jobs Pipelines | 348 jobs Terraform | 342 jobs Docker | 311 jobs Machine Learning | 309 jobs Linux | 265 jobs Azure | 256 jobs Computer Science | 246 jobs Ansible | 241 jobs Jenkins | 227 jobs Architecture | 214 jobs GCP | 193 jobs Agile | 189 jobs Git | 179 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 | 396 jobs Flex hours | 202 jobs Health care | 182 jobs Startup environment | 157 jobs Team events | 124 jobs Competitive pay | 118 jobs Equity / stock options | 110 jobs Flex vacation | 101 jobs Salary bonus | 67 jobs Medical leave | 64 jobs Insurance | 63 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

The salary for a DevOps Engineer transitioning into AI/ML/Data Science roles can vary significantly based on several factors such as region, industry, and company size. Typically, the compensation package is composed of a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, regions with a lower cost of living might offer a smaller base salary but compensate with substantial bonuses or stock options. Industries like finance or healthcare might offer higher bonuses due to the critical nature of data security and analysis in these fields. Larger companies often provide more comprehensive benefits and stock options, while startups might offer equity as a significant part of the compensation package.

Increasing Salary

To increase your salary from this position, consider specializing in a niche area within AI/ML or Data Science that is in high demand but has a limited supply of experts. This could include areas like natural language processing, computer vision, or AI ethics. Additionally, gaining experience in leadership roles or project management can make you eligible for higher-paying positions such as AI/ML team lead or data science manager. Networking within industry-specific conferences and meetups can also open doors to opportunities with higher compensation. Pursuing further education, such as a master's degree or Ph.D., can also lead to higher salary prospects.

Educational Requirements

Most positions in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve research or advanced algorithm development. Courses in statistics, machine learning, data mining, and big data technologies are particularly beneficial. Additionally, a strong foundation in programming languages such as Python, R, or Java is essential.

Helpful Certifications

Certifications can be a valuable addition to your resume, demonstrating your commitment to continuous learning and expertise in specific areas. Some common and helpful certifications include:

• 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, making you a more attractive candidate for higher-paying roles.

Required Experience

Typically, employers look for candidates with at least 3-5 years of experience in DevOps or related fields, with a demonstrated understanding of AI/ML concepts and tools. Experience with cloud platforms, containerization, and orchestration tools like Docker and Kubernetes is often required. Additionally, hands-on experience with data analysis, model training, and deployment in a production environment is highly valued.

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