Full Stack Engineer Salary in 2024

Salary details

The average Full Stack Engineer salary lies between USD 130,900 and USD 205,000 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: Dec. 15, 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 | 189 jobs React | 177 jobs Engineering | 175 jobs Machine Learning | 174 jobs APIs | 143 jobs JavaScript | 114 jobs AWS | 112 jobs Computer Science | 103 jobs Docker | 99 jobs Testing | 93 jobs Architecture | 92 jobs Agile | 86 jobs Node.js | 79 jobs Kubernetes | 78 jobs Java | 75 jobs Security | 67 jobs SQL | 64 jobs Pipelines | 64 jobs CI/CD | 64 jobs TypeScript | 59 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 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 | 159 jobs Startup environment | 97 jobs Health care | 89 jobs Flex hours | 88 jobs Equity / stock options | 66 jobs Competitive pay | 60 jobs Flex vacation | 47 jobs Team events | 39 jobs Parental leave | 38 jobs Insurance | 38 jobs Medical leave | 35 jobs Salary bonus | 30 jobs Fitness / gym | 28 jobs 401(k) matching | 25 jobs Home office stipend | 23 jobs Unlimited paid time off | 21 jobs Wellness | 16 jobs Relocation support | 16 jobs Gear | 11 jobs Conferences | 9 jobs

Salary Composition

The salary for a Full Stack Engineer specializing in AI/ML/Data Science typically comprises several components. The fixed base salary is the primary component, often making up 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10-20%. Additional remuneration might include stock options, especially in tech companies or startups, and other benefits like health insurance, retirement plans, and paid time off. The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York may offer higher base salaries and stock options, while smaller companies might provide more substantial bonuses to attract talent.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and frameworks. Specializing in niche areas like deep learning or natural language processing 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.
• Leadership Roles: Transitioning into a leadership or managerial position can significantly boost your salary.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.
• Certifications: Obtaining advanced certifications can demonstrate your expertise and commitment to the field, potentially leading to salary increases.

Educational Requirements

Most Full Stack Engineers in AI/ML/Data Science roles hold at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree is often preferred, especially for roles that require a deep understanding of machine learning algorithms and data analysis. Some positions may also require coursework or experience in statistics, data mining, or software development.

Helpful Certifications

Several certifications can enhance your qualifications for this role:

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

These certifications can validate your skills and knowledge, making you a more competitive candidate.

Required Experience

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

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