Cloud Engineer Salary in United States during 2024

Salary details

The average Cloud Engineer salary lies between USD 100,000 and USD 170,000 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: Dec. 22, 2024

Top 20 Job Tags for Cloud Engineer roles

The three most common job tag items assiciated with Cloud Engineer job listings are Python, Engineering 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:

Python | 211 jobs Engineering | 194 jobs AWS | 183 jobs Security | 171 jobs Machine Learning | 167 jobs Azure | 156 jobs Architecture | 144 jobs Terraform | 135 jobs Computer Science | 134 jobs GCP | 126 jobs Kubernetes | 124 jobs CI/CD | 122 jobs DevOps | 121 jobs Docker | 114 jobs Pipelines | 110 jobs Agile | 103 jobs Java | 85 jobs Big Data | 75 jobs SQL | 66 jobs Jenkins | 62 jobs

Top 20 Job Perks/Benefits for Cloud Engineer roles

The three most common job benefits and perks assiciated with Cloud 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 | 197 jobs Health care | 93 jobs Flex hours | 77 jobs Team events | 52 jobs Equity / stock options | 51 jobs Startup environment | 50 jobs Competitive pay | 50 jobs Salary bonus | 42 jobs Insurance | 40 jobs Flex vacation | 37 jobs Parental leave | 28 jobs Medical leave | 27 jobs 401(k) matching | 18 jobs Wellness | 18 jobs Conferences | 16 jobs Relocation support | 13 jobs Transparency | 12 jobs Flexible spending account | 10 jobs Fitness / gym | 8 jobs Gear | 7 jobs

Salary Composition

In the United States, the salary composition for a Cloud Engineer specializing in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is often the largest component, accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies and can be a significant part of the compensation, especially in high-growth startups or established tech giants. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market.

Increasing Salary

To increase your salary further from this position, consider pursuing advanced certifications or specialized training in emerging AI/ML technologies. Networking within industry-specific groups and attending conferences can also open up opportunities for higher-paying roles. Additionally, gaining experience in managing larger projects or teams can position you for leadership roles, which typically come with higher compensation. Exploring opportunities in high-demand industries such as finance, healthcare, or autonomous systems can also lead to higher salaries due to the specialized nature of the work.

Educational Requirements

Most Cloud Engineer roles 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. can be advantageous, particularly for roles that involve complex data analysis or the development of new machine learning models. Advanced degrees can also provide a competitive edge in the job market and may lead to higher starting salaries.

Helpful Certifications

Certifications can be quite beneficial in this field. Some of the most recognized ones include:

• AWS Certified Solutions Architect: Demonstrates expertise in designing and deploying scalable systems on AWS.
• Google Professional Cloud Architect: Validates the ability to design and manage secure, scalable cloud architectures.
• Microsoft Certified: Azure Solutions Architect Expert: Focuses on designing and implementing solutions on Microsoft Azure.
• Certified Kubernetes Administrator (CKA): Useful for roles involving container orchestration.
• 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 cloud engineering or related fields. Experience with cloud platforms like AWS, Azure, or Google Cloud is essential. Familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn is also important. Experience in data engineering, data analysis, or software development can be beneficial, as these skills are often integral to the role.

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