Salary for Senior-level / Expert Solutions Engineer during 2024

Salary details

The average senior-level / expert Solutions Engineer salary lies between USD 131,000 and USD 220,000 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: Dec. 22, 2024

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

The three most common job tag items assiciated with senior-level / expert Solutions Engineer job listings are Python, Engineering 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:

Python | 203 jobs Engineering | 188 jobs Machine Learning | 137 jobs Architecture | 125 jobs Java | 100 jobs Spark | 96 jobs AWS | 94 jobs Big Data | 93 jobs Databricks | 88 jobs Excel | 87 jobs Azure | 85 jobs MLFlow | 85 jobs Computer Science | 82 jobs Scala | 77 jobs GCP | 72 jobs SQL | 71 jobs Data Analytics | 66 jobs Generative AI | 65 jobs Security | 58 jobs APIs | 53 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Solutions Engineer job listings are Career development, Health care and Team events. 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 | 156 jobs Health care | 102 jobs Team events | 70 jobs Insurance | 69 jobs Salary bonus | 59 jobs Wellness | 57 jobs Equity / stock options | 56 jobs Flex hours | 52 jobs Competitive pay | 48 jobs Parental leave | 42 jobs Startup environment | 42 jobs Medical leave | 42 jobs Flex vacation | 41 jobs Fitness / gym | 40 jobs Conferences | 19 jobs Transparency | 18 jobs 401(k) matching | 17 jobs Home office stipend | 16 jobs Gear | 15 jobs Signing bonus | 13 jobs

Salary Composition

The salary for a Senior-level/Expert Solutions 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%. Additional remuneration might include stock options, especially in tech companies, and other benefits like health insurance, retirement plans, and paid time off. The 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 192,000, consider pursuing leadership roles such as a Director of Solutions Engineering or transitioning into a specialized niche within AI/ML that commands higher pay. Networking within the industry and building a strong personal brand can also open doors to higher-paying opportunities. Additionally, gaining expertise in emerging technologies or methodologies can make you more valuable to employers. Negotiating your salary based on market research and your proven track record can also lead to higher compensation.

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 complex problem-solving and advanced technical skills. Continuous learning through online courses and workshops is also crucial to keep up with the rapidly evolving field.

Helpful Certifications

Certifications can enhance your credibility and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Solutions Architect (AWS, Google Cloud, or Azure)
• Certified Data Scientist (SAS, IBM, or other recognized institutions)
• Machine Learning Certifications (Coursera, edX, or Udacity)
• Professional Scrum Master or Agile Certified Practitioner for those involved in project management

These certifications can provide a competitive edge and are often recognized by employers as a testament to your skills and knowledge.

Required Experience

Typically, a Senior-level/Expert Solutions Engineer should have at least 7-10 years of experience in the field. This experience should include hands-on work with AI/ML technologies, data analysis, and software development. Experience in leading projects, managing teams, and working with cross-functional stakeholders is also highly valued. A proven track record of successful project delivery and problem-solving in complex environments is essential.

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