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

Salary details

The average mid-level / intermediate Engineer salary lies between USD 105,000 and USD 183,000 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: Feb. 23, 2025

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate 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 | 10634 jobs Python | 10361 jobs Machine Learning | 6866 jobs Computer Science | 6688 jobs SQL | 6469 jobs Pipelines | 5882 jobs AWS | 5141 jobs Architecture | 4783 jobs Security | 4278 jobs Testing | 3840 jobs Azure | 3744 jobs ETL | 3714 jobs Data pipelines | 3580 jobs Agile | 3499 jobs Research | 3245 jobs Java | 3223 jobs Spark | 2906 jobs GCP | 2716 jobs Big Data | 2704 jobs APIs | 2587 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Engineer job listings are Career development, Health care and Flex hours. 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 | 9147 jobs Health care | 4868 jobs Flex hours | 3435 jobs Equity / stock options | 3224 jobs Startup environment | 2864 jobs Competitive pay | 2840 jobs Team events | 2261 jobs Flex vacation | 2111 jobs Insurance | 2055 jobs Medical leave | 1943 jobs Salary bonus | 1925 jobs Parental leave | 1872 jobs Wellness | 1212 jobs 401(k) matching | 1104 jobs Relocation support | 669 jobs Conferences | 608 jobs Home office stipend | 572 jobs Unlimited paid time off | 468 jobs Fitness / gym | 457 jobs Transparency | 440 jobs

Salary Composition

In the United States, the salary composition for a mid-level AI/ML/Data Science engineer typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's profitability and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can be a significant part of the total compensation, especially in high-growth industries.

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 market. Industry-wise, tech companies, finance, and healthcare often offer higher compensation packages compared to academia or non-profit sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and bonuses.

Increasing Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud computing, and big data technologies. Specializing in a niche area can also make you more valuable.

• Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open up higher-paying opportunities and leadership roles.

• Networking: Building a strong professional network can lead to new job opportunities and insights into higher-paying roles.

• Leadership Roles: Transitioning into a managerial or lead role can significantly increase your salary. This often requires developing soft skills such as communication, project management, and team leadership.

• Industry Switch: Moving to a higher-paying industry, such as finance or tech, can also result in a salary increase.

Educational Requirements

Most mid-level AI/ML/Data Science positions require at least a bachelor's degree in a related field such as computer science, data science, mathematics, or engineering. However, many employers prefer candidates with a master's degree or higher, especially for roles that involve complex problem-solving and advanced algorithm development. A strong foundation in statistics, programming, and machine learning principles is essential.

Helpful Certifications

While not always mandatory, certain certifications can enhance your resume and demonstrate your expertise:

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

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

Experience Requirements

Typically, a mid-level position requires 3-5 years of relevant experience in AI/ML or data science roles. This experience should include hands-on work with data analysis, model development, and deployment. Experience with programming languages such as Python or R, and familiarity with machine learning frameworks like TensorFlow or PyTorch, is often expected. Additionally, experience in a specific industry can be beneficial, as it provides domain knowledge that can be crucial for certain roles.

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