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

πŸ’° The median Salary for Mid-level / Intermediate AI Engineer in United States during 2024 is USD 140,000

✏️ This salary info is based on 159 individual salaries reported during 2024

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Salary details

The average mid-level / intermediate AI Engineer salary lies between USD 100,000 and USD 172,000 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.

Job title
AI Engineer
Experience
Mid-level / Intermediate
Region
United States
Salary year
2024
Sample size
159
Top 10%
$ 250,000
Top 25%
$ 172,000
Median
$ 140,000
Bottom 25%
$ 100,000
Bottom 10%
$ 80,000

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:

Salary trend

Top 20 Job Tags for Mid-level / Intermediate AI Engineer roles

The three most common job tag items assiciated with mid-level / intermediate AI Engineer job listings are Python, Machine Learning and Engineering. 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 | 280 jobs Machine Learning | 274 jobs Engineering | 264 jobs Computer Science | 192 jobs LLMs | 165 jobs NLP | 151 jobs Generative AI | 147 jobs PyTorch | 142 jobs Research | 140 jobs AWS | 135 jobs TensorFlow | 130 jobs Azure | 128 jobs Architecture | 109 jobs Deep Learning | 102 jobs Pipelines | 100 jobs ML models | 95 jobs GCP | 82 jobs APIs | 81 jobs Java | 81 jobs Agile | 77 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate AI Engineer job listings are Career development, Health care 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 | 240 jobs Health care | 118 jobs Flex hours | 94 jobs Competitive pay | 73 jobs Equity / stock options | 71 jobs Startup environment | 57 jobs Parental leave | 52 jobs Flex vacation | 51 jobs Insurance | 45 jobs Team events | 43 jobs Medical leave | 42 jobs Wellness | 40 jobs 401(k) matching | 39 jobs Salary bonus | 22 jobs Fitness / gym | 20 jobs Transparency | 19 jobs Home office stipend | 19 jobs Conferences | 17 jobs Relocation support | 12 jobs Unlimited paid time off | 12 jobs

Salary Composition for Mid-level AI Engineer Roles

The salary for a mid-level AI Engineer in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can be a significant part of the total compensation, especially in high-growth industries.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, sectors like finance, healthcare, and technology often offer higher compensation packages compared to others due to the critical role AI plays in their operations.

Steps to Increase Salary from a Mid-level Position

To increase your salary from a mid-level AI Engineer position, consider the following strategies:

  • Skill Enhancement: Continuously update your skills with the latest AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.

  • Advanced Education: Pursuing a master's degree or Ph.D. in AI, machine learning, or data science can open up higher-paying opportunities and leadership roles.

  • Networking and Professional Visibility: Attend industry conferences, contribute to open-source projects, and publish research papers to increase your visibility and network within the AI community.

  • Leadership and Management Skills: Developing skills in project management and team leadership can position you for roles with greater responsibility and higher pay.

  • Company Change: Sometimes, moving to a different company, especially one that values AI expertise highly, can result in a significant salary increase.

Educational Requirements for Mid-level AI Engineer Roles

Most mid-level 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 is often preferred and can be a significant advantage. Coursework in machine learning, statistics, and data analysis is crucial. Additionally, a strong foundation in programming languages such as Python, R, or Java is essential.

Helpful Certifications for AI Engineers

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

  • Google Professional Machine Learning Engineer
  • Microsoft Certified: Azure AI Engineer Associate
  • IBM AI Engineering Professional Certificate
  • AWS Certified Machine Learning – Specialty

These certifications can validate your skills in specific platforms and tools, making you more competitive in the job market.

Experience Requirements for Mid-level AI Engineer Roles

Typically, a mid-level AI Engineer is expected to have 3 to 5 years of relevant experience. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in deploying AI solutions in production environments and working in cross-functional teams is also highly valued.

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