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

Salary details

The average mid-level / intermediate Software Engineer salary lies between USD 125,400 and USD 208,800 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: Jan. 12, 2025

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate Software 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 | 1596 jobs Python | 1572 jobs Machine Learning | 1340 jobs Computer Science | 1230 jobs Java | 766 jobs Architecture | 752 jobs Testing | 751 jobs Security | 709 jobs AWS | 665 jobs SQL | 562 jobs Agile | 538 jobs Pipelines | 526 jobs APIs | 521 jobs Research | 500 jobs Kubernetes | 480 jobs Azure | 448 jobs JavaScript | 443 jobs Linux | 371 jobs Docker | 370 jobs LLMs | 340 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Software 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 | 1512 jobs Health care | 792 jobs Equity / stock options | 670 jobs Startup environment | 469 jobs Flex hours | 435 jobs Competitive pay | 424 jobs Medical leave | 408 jobs Salary bonus | 349 jobs Insurance | 338 jobs Flex vacation | 300 jobs Team events | 297 jobs Parental leave | 290 jobs Wellness | 241 jobs 401(k) matching | 173 jobs Relocation support | 130 jobs Unlimited paid time off | 80 jobs Transparency | 75 jobs Home office stipend | 71 jobs Gear | 66 jobs Conferences | 61 jobs

Salary Composition

In the United States, the salary composition for a mid-level/intermediate AI/ML/Data Science role typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10% to 20%. Additional remuneration, such as stock options or equity, is more common in tech companies and startups, potentially making up 5% to 15% of the total package.

The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more substantial equity components, while companies in the finance or healthcare sectors might provide more generous bonuses. Larger companies often have more structured compensation packages, whereas startups might offer lower base salaries but higher equity stakes.

Increasing Salary

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

• Skill Enhancement: Continuously update and expand your skill set, particularly in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open doors to higher-level positions and salary brackets.

• Leadership Roles: Transitioning into leadership or managerial roles can significantly boost your earning potential. This might involve leading a team of data scientists or managing AI projects.

• Networking and Industry Engagement: Actively participate in industry conferences, workshops, and meetups to build a strong professional network. This can lead to opportunities in higher-paying roles or companies.

• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most mid-level AI/ML/Data Science positions require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, a master's degree is increasingly preferred, especially for roles involving complex data analysis or machine learning model development. Some positions may also value interdisciplinary degrees that combine technical skills with business acumen.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate 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 AI/ML/Data Science role requires 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and programming in languages such as Python or R. Experience with data visualization tools, cloud platforms, and big data technologies is also highly valued.

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