Salary for Senior-level / Expert Full Stack Engineer during 2024

Salary details

The average senior-level / expert Full Stack Engineer salary lies between USD 143,500 and USD 212,310 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. 22, 2024

Top 20 Job Tags for Senior-level / Expert Full Stack Engineer roles

The three most common job tag items assiciated with senior-level / expert Full Stack Engineer job listings are Python, React and Machine Learning. 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 | 109 jobs React | 105 jobs Machine Learning | 100 jobs Engineering | 98 jobs APIs | 87 jobs AWS | 74 jobs JavaScript | 64 jobs Architecture | 62 jobs Testing | 61 jobs Docker | 61 jobs Computer Science | 58 jobs Agile | 51 jobs Kubernetes | 50 jobs Java | 50 jobs Node.js | 49 jobs Angular | 43 jobs TypeScript | 40 jobs Security | 39 jobs Pipelines | 39 jobs CI/CD | 39 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Full Stack Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Full Stack Engineer job listings are Career development, Flex hours 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 | 88 jobs Flex hours | 53 jobs Startup environment | 53 jobs Health care | 49 jobs Equity / stock options | 47 jobs Flex vacation | 37 jobs Competitive pay | 30 jobs Medical leave | 26 jobs Parental leave | 25 jobs Team events | 25 jobs Insurance | 24 jobs Home office stipend | 19 jobs 401(k) matching | 18 jobs Salary bonus | 17 jobs Fitness / gym | 15 jobs Wellness | 13 jobs Unlimited paid time off | 13 jobs Gear | 10 jobs Relocation support | 10 jobs Travel | 8 jobs

Salary Composition

The salary for a Senior-level or Expert Full Stack Engineer in AI/ML/Data Science typically comprises a base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can be performance-based or company-wide, and they vary significantly depending on the company's financial health and individual performance. Additional remuneration might include stock options, which are more common in startups or large tech firms, and other benefits like health insurance, retirement plans, and paid time off.

The composition can vary by region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more lucrative stock options compared to other regions. In contrast, smaller companies or those in less competitive markets might offer lower base salaries but compensate with higher equity stakes or bonuses.

Increasing Salary Further

To increase your salary beyond the median of USD 161,760, consider the following strategies:

• Specialization: Develop expertise in niche areas of AI/ML, such as natural language processing, computer vision, or reinforcement learning, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a team lead or engineering manager, which typically come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and full-stack development. This could involve taking advanced courses or attending workshops and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during job offers or performance reviews.

Educational Requirements

Most senior-level positions in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex algorithm development or research. Advanced degrees can provide a deeper understanding of machine learning theories and practices, which is crucial for high-level positions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your commitment to the field. 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 can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.

Required Experience

Typically, a senior-level position requires at least 5-10 years of experience in software development, with a significant portion of that time spent working on AI/ML projects. Experience in full-stack development is also crucial, as it demonstrates your ability to handle both front-end and back-end tasks. Employers look for candidates who have successfully led projects, mentored junior engineers, and contributed to the strategic direction of their teams or companies.

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