Systems Engineer Salary in 2024

Salary details

The average Systems Engineer salary lies between USD 122,000 and USD 212,750 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: Dec. 15, 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 | 431 jobs Python | 380 jobs Machine Learning | 267 jobs Architecture | 256 jobs Testing | 241 jobs Computer Science | 235 jobs Security | 217 jobs Research | 150 jobs Linux | 119 jobs Matlab | 111 jobs AWS | 103 jobs Mathematics | 100 jobs Kubernetes | 97 jobs Agile | 91 jobs Physics | 90 jobs Java | 88 jobs PhD | 86 jobs Pipelines | 85 jobs Azure | 73 jobs Statistics | 73 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 | 325 jobs Health care | 239 jobs Equity / stock options | 173 jobs Insurance | 128 jobs Flex hours | 126 jobs Competitive pay | 117 jobs Flex vacation | 115 jobs Salary bonus | 106 jobs Medical leave | 103 jobs Startup environment | 101 jobs Team events | 99 jobs Parental leave | 92 jobs 401(k) matching | 62 jobs Wellness | 60 jobs Relocation support | 59 jobs Fertility benefits | 35 jobs Unlimited paid time off | 27 jobs Flexible spending account | 25 jobs Signing bonus | 23 jobs Conferences | 23 jobs

Salary Composition

The salary for a Systems Engineer in AI/ML/Data Science typically comprises 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. Performance bonuses can vary significantly, ranging from 10-20% of the base salary, depending on the company's performance and individual contributions. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can form a significant part of the total compensation package, especially in regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of equity but may compensate with higher base salaries or bonuses.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Systems Engineer, AI/ML Architect, or transitioning into management positions like AI/ML Team Lead. Specializing in high-demand areas such as deep learning, natural language processing, or AI ethics can also make you more valuable. Additionally, gaining experience in leading projects, improving your negotiation skills, and obtaining advanced certifications or degrees can significantly enhance your earning potential. Networking within the industry and staying updated with the latest trends and technologies can also open up opportunities for higher-paying roles.

Educational Requirements

Most positions in AI/ML/Data Science for Systems Engineers 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 involving complex algorithm development or research. These advanced degrees provide a deeper understanding of machine learning models, data analysis, and system design, which are crucial for success in this field.

Helpful Certifications

Certifications can be a valuable addition to your resume, demonstrating your expertise and commitment to the field. Some common and helpful certifications include:

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

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

Required Experience

Typically, a Systems Engineer in AI/ML/Data Science is expected to have 3-5 years of experience in related fields. This experience should include hands-on work with machine learning models, data analysis, and system integration. Experience in software development, cloud computing, and working with large datasets is also highly valued. For more senior roles, 5-10 years of experience, including leadership or project management experience, may be required.

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