Systems Engineer Salary in United States during 2024

Salary details

The average Systems Engineer salary lies between USD 122,400 and USD 213,000 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 Systems Engineer roles

The three most common job tag items assiciated with Systems Engineer job listings are Engineering, Python and Machine Learning. 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:

Engineering | 438 jobs Python | 388 jobs Machine Learning | 273 jobs Architecture | 261 jobs Testing | 244 jobs Computer Science | 240 jobs Security | 220 jobs Research | 153 jobs Linux | 120 jobs Matlab | 115 jobs AWS | 105 jobs Mathematics | 103 jobs Kubernetes | 97 jobs Physics | 94 jobs Agile | 93 jobs PhD | 88 jobs Java | 88 jobs Pipelines | 87 jobs Robotics | 76 jobs Statistics | 75 jobs

Top 20 Job Perks/Benefits for Systems Engineer roles

The three most common job benefits and perks assiciated with Systems Engineer job listings are Career development, Health care and Equity / stock options. 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 | 333 jobs Health care | 245 jobs Equity / stock options | 176 jobs Flex hours | 130 jobs Insurance | 130 jobs Competitive pay | 119 jobs Flex vacation | 118 jobs Salary bonus | 108 jobs Medical leave | 106 jobs Startup environment | 104 jobs Team events | 101 jobs Parental leave | 96 jobs 401(k) matching | 62 jobs Wellness | 61 jobs Relocation support | 59 jobs Fertility benefits | 35 jobs Unlimited paid time off | 28 jobs Flexible spending account | 25 jobs Signing bonus | 23 jobs Conferences | 23 jobs

Salary Composition

In the United States, the salary composition for a Systems Engineer specializing in AI/ML/Data Science can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components:

• Base Salary: This is the fixed annual salary 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.

• Bonus: Bonuses can be performance-based or company-wide and are often paid annually. They can range from 10% to 20% of the base salary, depending on the company's performance and individual contributions.

• Additional Remuneration: This includes stock options, equity, or restricted stock units (RSUs), which are common in tech companies, especially startups. Benefits such as health insurance, retirement plans, and other perks also form part of the total compensation package.

Increasing Salary

To increase your salary from a Systems Engineer position in AI/ML/Data Science, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing a master's or Ph.D. in a related field can open doors to higher-paying roles and leadership positions.

• Networking: Engage with professional networks and communities. Attending conferences, meetups, and workshops can lead to new opportunities and insights into higher-paying roles.

• Leadership Roles: Transitioning into managerial or lead roles can significantly increase your earning potential. This might involve managing teams, projects, or entire departments.

Educational Requirements

Most Systems Engineer roles in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for more advanced positions. A strong foundation in mathematics, statistics, and programming is essential.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Machine Learning Professional (CMLP)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills and knowledge in specific platforms and tools, making you more attractive to potential employers.

Experience Requirements

Typically, employers look for candidates with 3-5 years of experience in related fields. This experience should include hands-on work with AI/ML models, data analysis, and software development. Experience in deploying machine learning models in production environments is highly valued.

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