Solutions Engineer Salary in 2024

Salary details

The average Solutions Engineer salary lies between USD 110,000 and USD 200,000 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. 15, 2024

Top 20 Job Tags for Solutions Engineer roles

The three most common job tag items assiciated with 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 | 348 jobs Engineering | 337 jobs Machine Learning | 263 jobs Architecture | 185 jobs Computer Science | 179 jobs Java | 168 jobs Big Data | 130 jobs AWS | 129 jobs SQL | 127 jobs GCP | 116 jobs Azure | 116 jobs Spark | 108 jobs Generative AI | 103 jobs Data Analytics | 101 jobs Security | 101 jobs Databricks | 99 jobs Research | 97 jobs JavaScript | 94 jobs APIs | 94 jobs Excel | 92 jobs

Top 20 Job Perks/Benefits for Solutions Engineer roles

The three most common job benefits and perks assiciated with 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 | 296 jobs Health care | 185 jobs Team events | 123 jobs Equity / stock options | 120 jobs Insurance | 97 jobs Startup environment | 95 jobs Salary bonus | 95 jobs Competitive pay | 93 jobs Flex hours | 92 jobs Wellness | 89 jobs Parental leave | 83 jobs Medical leave | 81 jobs Flex vacation | 72 jobs Fitness / gym | 49 jobs 401(k) matching | 46 jobs Conferences | 32 jobs Transparency | 26 jobs Home office stipend | 22 jobs Gear | 21 jobs Unlimited paid time off | 20 jobs

Salary Composition

The salary for a Solutions Engineer in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, accounting for 60-80% of the total compensation package. Performance bonuses can vary significantly, ranging from 10-20% of the total salary, depending on individual and company performance. Additional remuneration, such as stock options, profit-sharing, or benefits like health insurance and retirement plans, can make up the remaining 10-20%.

Regional differences play a significant role in salary composition. For instance, positions in tech hubs like Silicon Valley or New York City may offer higher base salaries and stock options due to the high cost of living and competitive job market. Industry and company size also influence salary composition. Larger tech companies or those in high-demand industries may offer more substantial bonuses and stock options compared to smaller firms or those in less competitive sectors.

Increasing Salary

To increase your salary from a Solutions Engineer position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, particularly in emerging AI/ML technologies and tools. This can make you more valuable to your current employer or attractive to potential employers.

• Advanced Education: Pursuing advanced degrees, such as a Master's or Ph.D. in a relevant field, can open up higher-paying opportunities and leadership roles.

• Networking: Build a strong professional network within the industry. Networking can lead to new job opportunities, collaborations, and insights into salary trends.

• Performance Excellence: Consistently exceed performance expectations and take on challenging projects. Demonstrating your impact on the company's success can justify salary increases or promotions.

• Negotiation Skills: Develop strong negotiation skills to effectively advocate for higher compensation during performance reviews or when considering new job offers.

Educational Requirements

Most Solutions Engineer positions in AI/ML/Data Science require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Engineering, or Mathematics. However, many employers prefer candidates with a master's degree or higher, especially for more senior roles. A strong educational background provides the foundational knowledge necessary to understand complex AI/ML concepts and apply them effectively in real-world scenarios.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Data Scientist (CDS)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications validate your skills in specific tools and platforms, making you a more competitive candidate.

Required Experience

Typically, a Solutions Engineer in AI/ML/Data Science is expected to have 3-5 years of relevant experience. This experience should include hands-on work with AI/ML technologies, data analysis, and software development. Experience in customer-facing roles or project management can also be beneficial, as these positions often require collaboration with clients and cross-functional teams to deliver tailored solutions.

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