Salary for Mid-level / Intermediate Full Stack Developer during 2024

Salary details

The average mid-level / intermediate Full Stack Developer salary lies between USD 91,997 and USD 150,000 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: Nov. 17, 2024

Top 20 Job Tags for Mid-level / Intermediate Full Stack Developer roles

The three most common job tag items assiciated with mid-level / intermediate Full Stack Developer job listings are Python, Engineering and APIs. 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 | 42 jobs Engineering | 36 jobs APIs | 30 jobs JavaScript | 29 jobs React | 29 jobs Agile | 27 jobs Computer Science | 26 jobs Machine Learning | 24 jobs Git | 24 jobs SQL | 21 jobs Architecture | 21 jobs Docker | 21 jobs Java | 21 jobs AWS | 20 jobs Security | 20 jobs Testing | 17 jobs PostgreSQL | 17 jobs Microservices | 16 jobs Node.js | 16 jobs Kubernetes | 15 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Full Stack Developer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Full Stack Developer job listings are Career development, Flex hours 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 | 35 jobs Flex hours | 19 jobs Health care | 13 jobs Startup environment | 12 jobs Team events | 7 jobs Insurance | 6 jobs 401(k) matching | 5 jobs Flex vacation | 5 jobs Medical leave | 5 jobs Salary bonus | 5 jobs Equity / stock options | 4 jobs Parental leave | 4 jobs Competitive pay | 3 jobs Flexible spending account | 3 jobs Wellness | 2 jobs Relocation support | 2 jobs Fitness / gym | 1 jobs Conferences | 1 jobs

Salary Composition

The salary for a mid-level AI/ML/Data Science role typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The composition can vary significantly based on region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but companies often offer substantial stock options as part of the compensation package. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with higher bonuses. Industries such as finance or healthcare may offer higher bonuses due to the critical nature of data-driven insights in these fields. Larger companies might provide more comprehensive benefits and stock options, while startups might offer equity as a significant part of the package to attract talent.

Increasing Salary

To increase your salary from this position, consider specializing in a niche area within AI/ML, such as natural language processing or computer vision, which are in high demand. Pursuing leadership roles, such as a team lead or project manager, can also lead to higher compensation. Additionally, gaining expertise in emerging technologies like quantum computing or blockchain as they relate to AI can set you apart. Networking within industry-specific conferences and meetups can open doors to higher-paying opportunities. Finally, consider relocating to regions with a higher demand for AI/ML professionals, where salaries are typically more competitive.

Educational Requirements

Most mid-level AI/ML/Data Science positions require at least a bachelor's degree in computer science, data science, mathematics, or a related field. However, a master's degree or Ph.D. can be advantageous, especially for roles that involve complex algorithm development or research. Employers often look for candidates with a strong foundation in statistics, machine learning, and programming languages such as Python or R. Practical experience through internships or projects is highly valued, as it demonstrates the ability to apply theoretical knowledge to real-world problems.

Helpful Certifications

Certifications can enhance your resume and demonstrate your commitment to professional development. Some valuable certifications include:

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

These certifications validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level position requires 3-5 years of experience in software development, with a focus on AI/ML or data science projects. Experience in full-stack development is beneficial, as it demonstrates your ability to integrate AI/ML solutions into broader applications. Employers look for candidates who have worked on end-to-end machine learning projects, from data collection and preprocessing to model deployment and monitoring. Experience with cloud platforms like AWS, Azure, or Google Cloud is often required, as many AI/ML solutions are deployed in cloud environments.

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