Full Stack Engineer Salary in United States during 2024

Salary details

The average Full Stack Engineer salary lies between USD 140,000 and USD 209,800 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: Dec. 22, 2024

Top 20 Job Tags for Full Stack Engineer roles

The three most common job tag items assiciated with Full Stack Engineer job listings are Python, React and Engineering. 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 | 192 jobs React | 180 jobs Engineering | 178 jobs Machine Learning | 176 jobs APIs | 146 jobs JavaScript | 115 jobs AWS | 113 jobs Computer Science | 106 jobs Docker | 99 jobs Testing | 95 jobs Architecture | 92 jobs Agile | 86 jobs Node.js | 80 jobs Kubernetes | 78 jobs Java | 76 jobs Security | 67 jobs SQL | 66 jobs Pipelines | 66 jobs CI/CD | 65 jobs TypeScript | 60 jobs

Top 20 Job Perks/Benefits for Full Stack Engineer roles

The three most common job benefits and perks assiciated with Full Stack Engineer job listings are Career development, Startup environment 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 | 162 jobs Startup environment | 97 jobs Flex hours | 89 jobs Health care | 89 jobs Equity / stock options | 67 jobs Competitive pay | 61 jobs Flex vacation | 47 jobs Team events | 40 jobs Parental leave | 39 jobs Insurance | 38 jobs Medical leave | 35 jobs Salary bonus | 30 jobs Fitness / gym | 28 jobs 401(k) matching | 25 jobs Home office stipend | 24 jobs Unlimited paid time off | 22 jobs Wellness | 16 jobs Relocation support | 16 jobs Gear | 11 jobs Conferences | 9 jobs

Salary Composition

In the United States, the salary composition for a Full Stack Engineer specializing in AI/ML/Data Science can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components:

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In tech hubs like Silicon Valley, New York, or Seattle, the base salary tends to be higher due to the cost of living and competitive job market.

• Bonus: Bonuses can be performance-based or company-wide and are often paid annually. They can range from 5% to 20% of the base salary, depending on the company's performance and individual contributions.

• Additional Remuneration: This includes stock options, equity, or profit-sharing plans, which are more common in startups or tech giants. These can significantly increase total compensation, especially if the company performs well.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML and data science. Specializing in niche areas like deep learning, natural language processing, or cloud-based AI solutions can make you more valuable.

• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open doors to higher-paying roles and leadership positions.

• Networking and Industry Engagement: Attend conferences, workshops, and meetups to connect with industry leaders and peers. This can lead to new opportunities and insights into higher-paying roles.

• Leadership Roles: Aim for positions that involve team leadership or project management, as these often come with higher compensation.

Educational Requirements

Most Full Stack Engineers in AI/ML/Data Science roles hold at least a bachelor's degree in computer science, software engineering, data science, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for roles that require deep expertise in AI/ML.

Helpful Certifications

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

• Certified Machine Learning Professional (CMLP)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills and knowledge, making you a more attractive candidate to potential employers.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in software development, with a focus on full-stack development and AI/ML projects. Experience with data analysis, model building, and deployment in production environments is highly valued. Additionally, familiarity with cloud platforms and DevOps practices can be beneficial.

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