Salary for Senior-level / Expert Systems Engineer during 2024

Salary details

The average senior-level / expert Systems Engineer salary lies between USD 129,000 and USD 216,000 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: Nov. 24, 2024

Top 20 Job Tags for Senior-level / Expert Systems Engineer roles

The three most common job tag items assiciated with senior-level / expert 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 | 237 jobs Python | 207 jobs Machine Learning | 142 jobs Architecture | 139 jobs Testing | 138 jobs Computer Science | 129 jobs Security | 125 jobs Research | 78 jobs AWS | 64 jobs Linux | 63 jobs Mathematics | 63 jobs Kubernetes | 60 jobs PhD | 60 jobs Matlab | 54 jobs Agile | 53 jobs Java | 53 jobs Azure | 48 jobs Docker | 48 jobs Physics | 48 jobs Pipelines | 46 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Systems Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 | 176 jobs Health care | 131 jobs Equity / stock options | 107 jobs Insurance | 71 jobs Startup environment | 68 jobs Flex vacation | 66 jobs Competitive pay | 65 jobs Medical leave | 65 jobs Salary bonus | 61 jobs Flex hours | 60 jobs Parental leave | 56 jobs Team events | 48 jobs 401(k) matching | 36 jobs Wellness | 35 jobs Relocation support | 32 jobs Fertility benefits | 25 jobs Unlimited paid time off | 18 jobs Flexible spending account | 16 jobs Lunch / meals | 12 jobs Signing bonus | 11 jobs

Salary Composition

The salary for a Senior-level or Expert Systems Engineer in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20% of the salary. Additional remuneration might include stock options, especially in tech companies, and other benefits such as health insurance, retirement contributions, and paid time off. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech giants in Silicon Valley might offer substantial stock options, while companies in other regions might focus more on cash bonuses.

Increasing Salary Further

To increase your salary beyond the median of USD 165,900, consider pursuing leadership roles such as a Director of Engineering or a Chief Technology Officer (CTO) position. These roles often come with higher compensation packages. Additionally, specializing in a niche area of AI/ML, such as natural language processing or computer vision, can make you more valuable. Networking within industry circles and attending conferences can also open up opportunities for higher-paying roles. Finally, consider negotiating your salary by demonstrating your impact on the company's bottom line or by leveraging offers from other companies.

Educational Requirements

Most senior-level positions 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. is often preferred, especially for roles that involve research or advanced technical work. These advanced degrees provide a deeper understanding of complex algorithms and data structures, which are crucial for high-level problem-solving in AI/ML.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise. Certifications such as the Certified Data Scientist (CDS), TensorFlow Developer Certificate, or AWS Certified Machine Learning – Specialty can be beneficial. These certifications validate your skills in specific tools and platforms commonly used in the industry, making you a more attractive candidate to potential employers.

Required Experience

Typically, a senior-level position in this field requires at least 5-10 years of experience in systems engineering, with a significant portion of that time spent working on AI/ML projects. Experience in leading teams, managing projects, and developing large-scale systems is often necessary. Employers look for candidates who have a proven track record of successfully deploying AI/ML solutions in real-world scenarios.

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