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

Salary details

The average mid-level / intermediate Engineer salary lies between USD 104,550 and USD 180,200 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: Dec. 22, 2024

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 | 10892 jobs Python | 10566 jobs Machine Learning | 7062 jobs Computer Science | 6720 jobs SQL | 6583 jobs Pipelines | 5960 jobs AWS | 5338 jobs Architecture | 4909 jobs Security | 4463 jobs Testing | 4018 jobs Azure | 3792 jobs ETL | 3770 jobs Agile | 3749 jobs Data pipelines | 3627 jobs Java | 3359 jobs Research | 3261 jobs Spark | 2999 jobs GCP | 2764 jobs Big Data | 2762 jobs APIs | 2633 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 | 9378 jobs Health care | 4953 jobs Flex hours | 3422 jobs Equity / stock options | 3293 jobs Competitive pay | 2907 jobs Startup environment | 2866 jobs Team events | 2324 jobs Flex vacation | 2100 jobs Insurance | 2074 jobs Salary bonus | 1946 jobs Medical leave | 1938 jobs Parental leave | 1868 jobs Wellness | 1286 jobs 401(k) matching | 1098 jobs Relocation support | 667 jobs Conferences | 606 jobs Home office stipend | 570 jobs Unlimited paid time off | 466 jobs Fitness / gym | 456 jobs Transparency | 438 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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