Salary for Mid-level / Intermediate AI Engineer in United States during 2023

Salary details

The average mid-level / intermediate AI Engineer salary lies between USD 140,000 and USD 175,000 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: Nov. 17, 2024

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 Machine Learning, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Machine Learning | 24 jobs Python | 22 jobs Engineering | 21 jobs TensorFlow | 15 jobs Computer Science | 15 jobs PyTorch | 14 jobs Deep Learning | 12 jobs NLP | 11 jobs Research | 11 jobs Statistics | 11 jobs R | 8 jobs AWS | 8 jobs GCP | 8 jobs Keras | 7 jobs Scikit-learn | 7 jobs ML models | 7 jobs Agile | 7 jobs Mathematics | 7 jobs Pandas | 6 jobs Architecture | 6 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 Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 23 jobs Health care | 11 jobs Startup environment | 9 jobs Competitive pay | 9 jobs Team events | 8 jobs Flex vacation | 7 jobs Equity / stock options | 6 jobs Flex hours | 5 jobs Wellness | 3 jobs Conferences | 3 jobs Relocation support | 3 jobs Medical leave | 3 jobs Insurance | 3 jobs Parental leave | 2 jobs Gear | 2 jobs Fitness / gym | 2 jobs Salary bonus | 2 jobs Home office stipend | 2 jobs 401(k) matching | 1 jobs Lunch / meals | 1 jobs

Salary Composition

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 profitability and individual performance metrics. Additional remuneration, like stock options, is more common in larger tech companies or startups, where equity is used as an incentive to align employee interests with company growth. 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 markets. Industry-wise, sectors like finance and healthcare may offer higher bonuses due to the critical nature of AI applications in these fields.

Increasing Salary

To increase your salary from a mid-level position, consider pursuing advanced roles such as Senior AI Engineer, AI Architect, or AI Team Lead. These positions often require a deeper understanding of AI systems, leadership skills, and the ability to manage projects or teams. Gaining expertise in high-demand areas like deep learning, natural language processing, or AI ethics can also make you more valuable. Networking within the industry, attending conferences, and contributing to open-source projects can enhance your visibility and open up opportunities for higher-paying roles. Additionally, negotiating your salary during performance reviews or when switching jobs can lead to significant increases.

Educational Requirements

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 or Ph.D. can be advantageous and sometimes necessary, especially for roles that involve research or advanced algorithm development. A strong foundation in mathematics, statistics, and programming is essential, as these skills are critical for developing and implementing AI models.

Helpful Certifications

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

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

Required Experience

Typically, a mid-level AI Engineer is expected to have 3-5 years of experience in AI or related fields. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience with popular AI frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Additionally, familiarity with cloud platforms such as AWS, Azure, or Google Cloud can be beneficial, as many AI solutions are deployed in cloud environments.

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