Fullstack Engineer Salary in 2024

Salary details

The average Fullstack Engineer salary lies between USD 137,781 and USD 215,424 globally. 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.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 17, 2024

Top 20 Job Tags for Fullstack Engineer roles

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

Engineering | 59 jobs React | 59 jobs Python | 50 jobs JavaScript | 44 jobs TypeScript | 43 jobs Research | 38 jobs Machine Learning | 35 jobs APIs | 35 jobs Architecture | 34 jobs Kubernetes | 30 jobs Testing | 29 jobs LLMs | 29 jobs AWS | 25 jobs Security | 24 jobs Node.js | 24 jobs Privacy | 24 jobs Docker | 23 jobs Angular | 23 jobs GraphQL | 21 jobs Pipelines | 21 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 Health care. 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 | 58 jobs Equity / stock options | 48 jobs Health care | 47 jobs Startup environment | 47 jobs Competitive pay | 40 jobs Medical leave | 31 jobs Parental leave | 27 jobs Team events | 26 jobs Flex hours | 25 jobs Flex vacation | 22 jobs Insurance | 19 jobs Salary bonus | 18 jobs 401(k) matching | 14 jobs Home office stipend | 7 jobs Fitness / gym | 6 jobs Wellness | 5 jobs Transparency | 5 jobs Unlimited paid time off | 5 jobs Gear | 2 jobs Conferences | 2 jobs

Salary Composition

The salary for a Fullstack Engineer specializing in AI/ML/Data Science can vary significantly based on several factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, a performance-based bonus, and additional remuneration such as stock options or equity, especially in tech startups or large tech companies. In regions like Silicon Valley, the base salary might be higher due to the cost of living, while bonuses and stock options can form a significant part of the total compensation package. In contrast, companies in other regions might offer a lower base salary but compensate with higher bonuses or other benefits. Industries such as finance or healthcare might offer higher salaries due to the specialized nature of the work and the critical impact of AI/ML solutions in these fields.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Lead Engineer, AI/ML Architect, or transitioning into management positions like Engineering Manager or Director of Engineering. Gaining expertise in emerging technologies or niche areas within AI/ML can also make you more valuable. Additionally, building a strong portfolio of successful projects, contributing to open-source projects, or publishing research can enhance your reputation and bargaining power. Networking within industry circles and attending conferences can also open up opportunities for higher-paying roles.

Educational Requirements

Most positions for a Fullstack Engineer in AI/ML/Data Science require at least a bachelor's degree in computer science, software engineering, or a related field. However, a master's degree or Ph.D. in a specialized area such as machine learning, data science, or artificial intelligence can be highly advantageous and sometimes necessary for more advanced roles. Employers often look for candidates with a strong foundation in mathematics, statistics, and programming.

Helpful Certificates

While not always mandatory, certain certifications can bolster your credentials and demonstrate your expertise. Certifications such as the Google Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, or Microsoft Certified: Azure AI Engineer Associate are well-regarded in the industry. Additionally, completing courses from platforms like Coursera, edX, or Udacity in AI/ML can also be beneficial.

Experience Requirements

Typically, employers look for candidates with at least 3-5 years of experience in software development, with a focus on fullstack development and some exposure to AI/ML projects. Experience with popular programming languages such as Python, JavaScript, or Java, and familiarity with AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn is often required. Experience in deploying machine learning models and working with cloud platforms like AWS, Azure, or Google Cloud is also highly valued.

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