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

Salary details

The average mid-level / intermediate Cloud Engineer salary lies between USD 97,097 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: Nov. 17, 2024

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

The three most common job tag items assiciated with mid-level / intermediate Cloud Engineer job listings are Python, AWS and Security. 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 | 43 jobs AWS | 42 jobs Security | 41 jobs Architecture | 37 jobs Engineering | 36 jobs Machine Learning | 35 jobs Azure | 33 jobs GCP | 31 jobs Terraform | 31 jobs Computer Science | 27 jobs CI/CD | 26 jobs Kubernetes | 25 jobs Pipelines | 24 jobs Docker | 22 jobs DevOps | 22 jobs Big Data | 20 jobs Linux | 17 jobs Agile | 17 jobs Java | 16 jobs Testing | 15 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 38 jobs Health care | 24 jobs Flex hours | 19 jobs Startup environment | 15 jobs Competitive pay | 12 jobs Insurance | 12 jobs Equity / stock options | 11 jobs Salary bonus | 10 jobs Flex vacation | 7 jobs Wellness | 6 jobs Relocation support | 6 jobs Conferences | 5 jobs Team events | 5 jobs Medical leave | 5 jobs Fitness / gym | 4 jobs Transparency | 3 jobs 401(k) matching | 2 jobs Parental leave | 2 jobs Flat hierarchy | 1 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Cloud Engineer in AI/ML/Data Science typically includes a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. In tech hubs like Silicon Valley, Seattle, or New York, bonuses might be more substantial compared to other regions. Additional remuneration can include stock options, especially in tech companies, and benefits like health insurance, retirement plans, and paid time off. Larger companies or those in highly competitive industries may offer more comprehensive packages compared to smaller firms.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in AI/ML and cloud technologies. Specializing in emerging areas like AI ethics, machine learning operations (MLOps), or edge computing can make you more valuable.
• Advanced Certifications: Obtain advanced certifications in cloud platforms (AWS, Azure, Google Cloud) or in AI/ML specializations.
• Networking: Engage with professional networks and communities. Attend conferences, webinars, and workshops to connect with industry leaders and peers.
• Leadership Roles: Aim for leadership or managerial roles that offer higher pay scales. Demonstrating leadership skills can position you for promotions.
• Industry Shift: Consider moving to industries that pay higher for AI/ML expertise, such as finance, healthcare, or autonomous vehicles.

Educational Requirements

Most positions for a Mid-level/Intermediate Cloud Engineer in AI/ML/Data Science require at least a bachelor’s degree in computer science, data science, engineering, or a related field. However, a master’s degree can be advantageous and is often preferred by employers, especially for roles that involve complex data analysis or machine learning model development. Some positions may also value equivalent practical experience or a strong portfolio of projects.

Helpful Certifications

Certifications can significantly enhance your profile. Some valuable certifications include:

• Cloud Certifications: AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, Google Professional Cloud Architect.
• AI/ML Certifications: TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate.
• Data Science Certifications: Certified Data Scientist (CDS), IBM Data Science Professional Certificate.

Required Experience

Typically, a Mid-level/Intermediate Cloud Engineer in AI/ML/Data Science is expected to have 3-5 years of relevant experience. This experience should include hands-on work with cloud platforms, AI/ML model development, and data analysis. Experience in deploying machine learning models in a cloud environment and familiarity with DevOps practices can be particularly beneficial.

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