Salary for Mid-level / Intermediate Full Stack Engineer in United States during 2024

Salary details

The average mid-level / intermediate Full Stack Engineer salary lies between USD 125,000 and USD 180,000 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 Mid-level / Intermediate Full Stack Engineer roles

The three most common job tag items assiciated with mid-level / intermediate 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 | 51 jobs React | 51 jobs Machine Learning | 49 jobs Engineering | 49 jobs APIs | 38 jobs JavaScript | 34 jobs Docker | 27 jobs Computer Science | 25 jobs Agile | 24 jobs Testing | 21 jobs Node.js | 21 jobs Kubernetes | 20 jobs AWS | 20 jobs Security | 19 jobs DevOps | 19 jobs MongoDB | 17 jobs Flask | 17 jobs GitHub | 17 jobs CI/CD | 16 jobs Architecture | 15 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Full Stack Engineer job listings are Career development, Startup environment and Flex hours. 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 | 43 jobs Startup environment | 28 jobs Flex hours | 27 jobs Health care | 23 jobs Competitive pay | 16 jobs Insurance | 11 jobs Equity / stock options | 10 jobs Fitness / gym | 10 jobs Team events | 8 jobs Parental leave | 6 jobs Flex vacation | 6 jobs Salary bonus | 6 jobs Medical leave | 5 jobs Unlimited paid time off | 5 jobs Relocation support | 4 jobs Home office stipend | 3 jobs 401(k) matching | 2 jobs Wellness | 2 jobs Pet friendly | 2 jobs Flat hierarchy | 1 jobs

Salary Composition

In the United States, the salary composition for a mid-level/intermediate full-stack engineer specializing in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary package includes:

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In tech hubs like San Francisco, New York, or Seattle, the base salary might be higher due to the cost of living and competitive market rates.

• Bonus: Many companies offer performance-based bonuses, which can range from 5% to 20% of the base salary. These bonuses are often tied to individual performance, team success, or company profitability.

• Equity/Stock Options: Particularly in startups or tech companies, equity can be a significant part of the compensation package. This offers potential long-term financial benefits if the company performs well.

• Benefits and Perks: These can include health insurance, retirement plans (like 401(k) matching), paid time off, and other perks such as remote work options, wellness programs, and professional development allowances.

Increasing Salary Potential

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

• Specialize Further: Developing expertise in a niche area of AI/ML, such as natural language processing, computer vision, or reinforcement learning, can make you more valuable.

• Leadership Roles: Transitioning into a lead or managerial role can significantly boost your earning potential. This might involve managing a team of engineers or leading projects.

• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Attending workshops, conferences, and enrolling in advanced courses can enhance your skills and marketability.

• Networking: Building a strong professional network can open up opportunities for higher-paying positions. Engage with industry groups, attend meetups, and connect with peers on platforms like LinkedIn.

Educational Requirements

For a mid-level full-stack engineer role in AI/ML/Data Science, the most common educational requirements include:

• Bachelor’s Degree: Typically in Computer Science, Data Science, Mathematics, or a related field. This provides a solid foundation in programming, algorithms, and data structures.

• Master’s Degree: While not always required, a master’s degree in AI, Machine Learning, or Data Science can be advantageous and is often preferred by top-tier companies.

Helpful Certifications

Certifications can bolster your credentials and demonstrate your expertise. Some valuable certifications include:

• Certified Machine Learning Professional (CMLP): Validates your skills in machine learning techniques and tools.

• AWS Certified Machine Learning – Specialty: Demonstrates your ability to design, implement, and maintain machine learning solutions on AWS.

• Google Professional Machine Learning Engineer: Focuses on designing, building, and productionizing ML models using Google Cloud technologies.

Experience Requirements

Typically, a mid-level position requires:

• 3-5 Years of Experience: In software development, with a focus on full-stack engineering. Experience in AI/ML projects is highly beneficial.

• Project Experience: Demonstrated experience in building and deploying AI/ML models, working with data pipelines, and integrating these models into applications.

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