Salary for Senior-level / Expert Fullstack Engineer in United States during 2024

Salary details

The average senior-level / expert 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 Senior-level / Expert Fullstack Engineer roles

The three most common job tag items assiciated with senior-level / expert 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 | 45 jobs React | 42 jobs Python | 37 jobs JavaScript | 36 jobs TypeScript | 33 jobs Research | 30 jobs APIs | 28 jobs Machine Learning | 27 jobs Architecture | 26 jobs Testing | 25 jobs Angular | 21 jobs Kubernetes | 20 jobs LLMs | 20 jobs GraphQL | 18 jobs Pipelines | 18 jobs Privacy | 18 jobs AWS | 17 jobs Security | 17 jobs Node.js | 16 jobs Generative AI | 16 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert 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 | 45 jobs Equity / stock options | 40 jobs Health care | 34 jobs Startup environment | 34 jobs Competitive pay | 33 jobs Medical leave | 24 jobs Parental leave | 20 jobs Flex hours | 20 jobs Team events | 18 jobs Flex vacation | 16 jobs Insurance | 16 jobs Salary bonus | 14 jobs 401(k) matching | 12 jobs Fitness / gym | 6 jobs Wellness | 5 jobs Transparency | 5 jobs Home office stipend | 5 jobs Unlimited paid time off | 3 jobs Gear | 2 jobs Conferences | 2 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Fullstack Engineer in AI/ML/Data Science typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually make up about 10-20%. Additional remuneration, such as stock options or equity, can vary significantly depending on the company size and industry. For instance, tech giants and startups in Silicon Valley might offer substantial equity packages, whereas companies in other regions or industries might provide smaller equity components or none at all.

Increasing Salary Further

To increase your salary beyond the median of USD 182,750, consider the following strategies:

• Specialization: Develop expertise in niche areas within 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 offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and fullstack development. This can make you more valuable to your current or potential employers.
• Networking: Engage with professional networks and communities. Opportunities often arise through connections and referrals.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation 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 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 and knowledge in specific platforms or methodologies, making you more attractive to employers.

Required Experience

Typically, a senior-level fullstack engineer in AI/ML/Data Science is expected to have 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 both frontend and backend development, as well as a strong understanding of data structures, algorithms, and system design, is crucial. Additionally, hands-on experience with machine learning frameworks and tools, such as TensorFlow, PyTorch, or Scikit-learn, is often required.

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