Fullstack Engineer Salary in United States during 2024

Salary details

The average Fullstack Engineer salary lies between USD 150,000 and USD 217,900 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. 15, 2024

Top 20 Job Tags for Fullstack Engineer roles

The three most common job tag items assiciated with Fullstack Engineer job listings are React, Engineering and Python. 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:

React | 64 jobs Engineering | 61 jobs Python | 52 jobs TypeScript | 48 jobs JavaScript | 44 jobs Research | 39 jobs Machine Learning | 38 jobs Architecture | 38 jobs APIs | 37 jobs Kubernetes | 31 jobs LLMs | 31 jobs Testing | 29 jobs Node.js | 28 jobs AWS | 26 jobs Security | 24 jobs Docker | 24 jobs Privacy | 24 jobs Angular | 23 jobs GraphQL | 22 jobs Pipelines | 22 jobs

Top 20 Job Perks/Benefits for Fullstack Engineer roles

The three most common job benefits and perks assiciated with Fullstack Engineer job listings are Career development, Equity / stock options and Startup environment. 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 | 62 jobs Equity / stock options | 51 jobs Startup environment | 50 jobs Health care | 48 jobs Competitive pay | 43 jobs Medical leave | 32 jobs Parental leave | 28 jobs Team events | 27 jobs Flex hours | 25 jobs Flex vacation | 22 jobs Insurance | 19 jobs Salary bonus | 19 jobs 401(k) matching | 14 jobs Transparency | 7 jobs Home office stipend | 7 jobs Fitness / gym | 6 jobs Unlimited paid time off | 6 jobs Wellness | 5 jobs Gear | 2 jobs Conferences | 2 jobs

Salary Composition

In the United States, the salary for a Fullstack Engineer specializing in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up about 10-20%. Additional remuneration might include stock options, especially in tech companies or startups, and can account for 5-10% 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 stock options, while smaller companies might focus more on bonuses.

Next Steps for Salary Increase

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

• Specialization: Deepen your expertise in a niche area of AI/ML, such as natural language processing or computer vision, which can command higher salaries.
• Leadership Roles: Transition into roles like AI/ML team lead or architect, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive.
• Networking: Engage with industry professionals through conferences, meetups, and online platforms to discover new opportunities.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Fullstack Engineers in AI/ML/Data Science roles hold at least a bachelor's degree in computer science, data science, or a related field. However, a master's degree or Ph.D. can be advantageous, especially for roles that require deep technical expertise or research capabilities. Some positions may also value interdisciplinary degrees that combine computer science with fields like statistics or mathematics.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field:

• 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 in specific platforms or methodologies, making you more attractive to potential employers.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in software development, with a focus on fullstack engineering. Experience in AI/ML projects, either through professional work or significant personal projects, is highly valued. Familiarity with data science tools and frameworks, such as TensorFlow, PyTorch, or Scikit-learn, is often required.

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