Artificial Intelligence Engineer Salary in United States during 2024

Salary details

The average Artificial Intelligence Engineer salary lies between USD 94,600 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 Artificial Intelligence Engineer roles

The three most common job tag items assiciated with Artificial Intelligence Engineer job listings are Machine Learning, Engineering 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:

Machine Learning | 70 jobs Engineering | 54 jobs Python | 52 jobs Computer Science | 42 jobs ML models | 41 jobs Agile | 32 jobs Research | 30 jobs TensorFlow | 29 jobs PyTorch | 28 jobs MLOps | 27 jobs Azure | 26 jobs NLP | 23 jobs Pipelines | 21 jobs Deep Learning | 20 jobs Testing | 20 jobs Statistics | 20 jobs LLMs | 20 jobs AWS | 18 jobs Scrum | 18 jobs Architecture | 17 jobs

Top 20 Job Perks/Benefits for Artificial Intelligence Engineer roles

The three most common job benefits and perks assiciated with Artificial Intelligence Engineer job listings are Career development, Team events and Competitive pay. 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 | 70 jobs Team events | 28 jobs Competitive pay | 27 jobs Flex hours | 26 jobs Parental leave | 20 jobs Health care | 19 jobs Startup environment | 19 jobs Salary bonus | 17 jobs Medical leave | 12 jobs Insurance | 11 jobs Equity / stock options | 10 jobs Conferences | 9 jobs Flex vacation | 8 jobs Wellness | 8 jobs Flexible spending account | 5 jobs Signing bonus | 3 jobs 401(k) matching | 2 jobs Relocation support | 1 jobs Home office stipend | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

The salary for an Artificial Intelligence Engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. In tech hubs like Silicon Valley, bonuses and stock options can be substantial, reflecting the high demand for AI talent. In contrast, regions with a lower cost of living might offer smaller bonuses but still provide competitive base salaries. Larger companies or those in high-growth industries like tech or finance often offer more comprehensive compensation packages, including health benefits, retirement plans, and other perks.

Increasing Salary

To increase your salary from the median level, consider pursuing advanced roles such as Senior AI Engineer, AI Architect, or AI Team Lead. Gaining expertise in niche areas like deep learning, natural language processing, or computer vision can make you more valuable. Additionally, developing strong leadership and project management skills can position you for roles with greater responsibility and higher pay. Networking within the industry, attending conferences, and contributing to open-source projects can also enhance your visibility and open up opportunities for higher-paying positions.

Educational Requirements

Most AI Engineer 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. is often preferred, especially for roles involving complex research and development. Advanced degrees provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for developing sophisticated AI systems.

Helpful Certifications

While not always mandatory, certifications can bolster your credentials and demonstrate your expertise. Some valuable certifications include:

• Google Professional Machine Learning Engineer: Validates your ability to design, build, and productionize ML models.
• Microsoft Certified: Azure AI Engineer Associate: Focuses on using Azure services to build AI solutions.
• AWS Certified Machine Learning – Specialty: Demonstrates your ability to implement machine learning solutions on AWS.
• TensorFlow Developer Certificate: Shows proficiency in using TensorFlow for machine learning and deep learning tasks.

Required Experience

Typically, employers look for candidates with at least 2-5 years of experience in AI, machine learning, or data science roles. Experience with programming languages such as Python, R, or Java, and familiarity with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn, is often required. Experience in data preprocessing, model training, and deployment is also crucial. For senior roles, more extensive experience, including leading projects or teams, is often necessary.

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