Salary for Mid-level / Intermediate Solutions Engineer in United States during 2024

Salary details

The average mid-level / intermediate Solutions Engineer salary lies between USD 100,000 and USD 150,000 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: Nov. 3, 2024

Top 20 Job Tags for Mid-level / Intermediate Solutions Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Solutions 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 | 80 jobs Python | 74 jobs Machine Learning | 68 jobs Computer Science | 61 jobs Java | 34 jobs SQL | 31 jobs Consulting | 29 jobs Mathematics | 29 jobs Research | 28 jobs Architecture | 28 jobs Generative AI | 26 jobs JavaScript | 25 jobs GCP | 24 jobs Linux | 23 jobs PyTorch | 22 jobs TensorFlow | 21 jobs Transformers | 21 jobs APIs | 21 jobs Data Analytics | 20 jobs Google Cloud | 19 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Solutions Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Solutions 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 | 75 jobs Health care | 46 jobs Equity / stock options | 37 jobs Team events | 30 jobs Startup environment | 29 jobs Parental leave | 26 jobs 401(k) matching | 25 jobs Wellness | 25 jobs Medical leave | 22 jobs Salary bonus | 21 jobs Flex hours | 17 jobs Flex vacation | 17 jobs Competitive pay | 17 jobs Insurance | 10 jobs Conferences | 7 jobs Fitness / gym | 4 jobs Transparency | 4 jobs Unlimited paid time off | 4 jobs Flexible spending account | 3 jobs Gear | 2 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Solutions Engineer in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, usually making up 10% to 20% of the total compensation. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can account for 5% to 15% of the total package. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets.

Increasing Salary

To increase your salary from this position, consider the following steps:

• Skill Enhancement: Continuously update your technical skills, especially in emerging AI/ML technologies and tools. Specializing in a niche area can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into a leadership or managerial role can significantly boost your salary.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Certifications: Obtaining advanced certifications can demonstrate your expertise and commitment to the field, potentially leading to salary increases.

Educational Requirements

Most mid-level solutions engineer positions in AI/ML/Data Science require at least a bachelor's degree in computer science, data science, engineering, or a related field. However, many employers prefer candidates with a master's degree, especially for roles that involve complex problem-solving and advanced technical skills. 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 Data Scientist (CDS)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

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

Required Experience

Typically, a mid-level solutions engineer role requires 3 to 5 years of experience in a related field. 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 and collaborating with cross-functional teams is highly valued.

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