Salary for Mid-level / Intermediate DevOps Engineer in United States during 2024

Salary details

The average mid-level / intermediate DevOps Engineer salary lies between USD 97,335 and USD 180,000 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. 10, 2024

Top 20 Job Tags for Mid-level / Intermediate DevOps Engineer roles

The three most common job tag items assiciated with mid-level / intermediate DevOps Engineer job listings are DevOps, Python and AWS. 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 | 109 jobs Python | 100 jobs AWS | 84 jobs Kubernetes | 82 jobs Pipelines | 78 jobs CI/CD | 74 jobs Engineering | 70 jobs Security | 70 jobs Terraform | 70 jobs Linux | 64 jobs Ansible | 58 jobs Machine Learning | 56 jobs Docker | 53 jobs Azure | 49 jobs Architecture | 41 jobs GCP | 41 jobs Git | 40 jobs Jenkins | 40 jobs Agile | 38 jobs Computer Science | 38 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate DevOps Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate DevOps Engineer job listings are Career development, Health care and Flex hours. 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 | 72 jobs Health care | 40 jobs Flex hours | 39 jobs Startup environment | 27 jobs Equity / stock options | 19 jobs Competitive pay | 18 jobs Flex vacation | 16 jobs Medical leave | 15 jobs Salary bonus | 15 jobs Team events | 14 jobs Parental leave | 7 jobs Insurance | 7 jobs Unlimited paid time off | 7 jobs 401(k) matching | 5 jobs Fitness / gym | 5 jobs Conferences | 5 jobs Gear | 4 jobs Transparency | 4 jobs Wellness | 3 jobs Travel | 3 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate DevOps Engineer in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. This base salary can range from 70% to 85% of the total compensation. Bonuses, which can be performance-based or company-wide, often account for 10% to 20% of the total package. Additional remuneration may include stock options, especially in tech-heavy regions like Silicon Valley, and benefits such as health insurance, retirement contributions, and paid time off. Larger companies or those in high-cost living areas may offer more competitive packages, while smaller companies might compensate with equity or flexible work arrangements.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like MLOps or AI ethics can make you more valuable.
• Advanced Education: Pursuing a master's degree or relevant certifications can enhance your qualifications and open up higher-paying opportunities.
• Networking: Engage with professional communities and attend industry conferences to expand your network and learn about new opportunities.
• Leadership Roles: Seek opportunities to lead projects or teams, as managerial experience can significantly boost your earning potential.
• Switching Companies: Sometimes, moving to a new company can result in a substantial salary increase, especially if you leverage offers from multiple employers.

Educational Requirements

Most positions for a Mid-level/Intermediate DevOps Engineer in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, or a related field. However, a master's degree in data science, machine learning, or a related discipline can be advantageous and is often preferred by top-tier companies. Practical experience and a strong portfolio can sometimes offset the lack of an advanced degree.

Helpful Certifications

Certifications can bolster your credentials and demonstrate your 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): Shows expertise in managing Kubernetes clusters, which is crucial for MLOps.
• Microsoft Certified: Azure DevOps Engineer Expert: Highlights skills in combining people, processes, and technologies to deliver valuable products and services.

Required Experience

Typically, a Mid-level/Intermediate DevOps Engineer in AI/ML/Data Science is expected to have 3 to 5 years of relevant experience. This includes hands-on experience with cloud platforms, CI/CD pipelines, and infrastructure automation. Experience with AI/ML frameworks and tools, such as TensorFlow, PyTorch, or Scikit-learn, is also highly desirable.

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