In the fast-changing world of AI, understanding the difference between an artificial intelligence engineer and an artificial intelligence developer has become quite essential. As firms are striving to leverage the benefits of AI, it is important to upskill in the trending technologies. While both of these professions are designed to create AI solutions, each of them has a specific skill set. By understanding which of these roles will align with your career goals, you can make a mark in the job market.

In this blog, we will discuss the difference between an AI engineer and a developer by highlighting the key areas like job profile, work responsibilities, salary range, and important skills. It is followed by a brief discussion on AI Certifications and what other facts to consider for choosing the right field, helping you make the right decision for your future in AI.  

Differences Between an AI Developer and an AI Engineer

When comparing two significant AI professions, that is, Developer and Engineer, you will find numerous statistics that highlight the differences in these roles in terms of career prospects, skills, and responsibilities.

1.    Job Profile

To gain a better clarity on who is an AI engineer or an AI developer, here is a brief explanation.

·        AI Engineer:

o   These professionals are mainly focused on designing the necessary framework to support large-scale artificial intelligence solutions.

o   These engineers work with many advanced tools like TensorFlow, Kubernetes, Docker, and different cloud platforms like AWS, Google Cloud, etc.

o   Their work is important in almost all industries, such as healthcare, automobiles, finance, etc., due to the rapid integration of technologies.   

·        AI Developer:

o   This profession refers to those who are responsible for designing, managing, and deploying a system’s infrastructure to support large-scale artificial intelligence solutions.

o   Unlike AI engineers, they are not just responsible for designing but also creating effective software solutions that incorporate AI algorithms.

o   These developers rely on high-level programming languages like Python, Java, or C++ and leverage tools such as TensorFlow, Keras, or PyTorch to build and optimize AI solutions.

2.    Work Responsibilities

The key responsibilities for each of these professions are discussed below:

AI Developer:

·  Understanding Business Requirements – AI developers work closely with the stakeholders to work as per the business guidelines or requirements. Hence, one of their objectives is to analyze the business needs and define the problem statement through AI solutions.

·        Data Collection and Preparation – One of the key responsibilities of an AI developer is to collect and process sample data to ensure quality, relevance, and completeness to the problem in hand. Therefore, with the clean and effective data, they can give accurate results.

AI Engineer:

·     Optimization of Machine Learning Models – These engineers optimize AI model algorithms for enhancing scalability, which is done by leveraging advanced techniques like pruning, parallel computing, quantization, etc.

·        Designing Infrastructure and Data Pipelines – According to a recent report, it is found that data pipelines reduce the time speed for data preparation by 70% (IBM). AI engineers are skilled in creating effective data pipelines that further facilitate data preparation and data modeling.

3.    Salary Range

Salary is an essential factor of differentiation for professionals, especially in competitive fields in AI. Here is detailed information on the salary brackets for these two professions.

·        As per the recent data collected from LinkedIn, the average salary per year of an AI developer in the United States ranges around $129,348, which is approximately $62.19 per hour (LinkedIn).

·        On the other hand, for artificial intelligence engineers, the entry-level salary is around $80,000; however, for the experienced professionals (who have more than 6 years of work experience), they have an earning potential of up to $176,250.

4.    Skills Required

As you can understand from the above information, both AI developers and AI engineers have created a dependency in firms irrespective of the sector. Hence, to create that value in a firm, you need to have certain AI skills.

AI Developer:  

Ø  Understanding machine learning algorithms

Ø  Familiarity with AI frameworks

Ø  Knowledge of Deep learning techniques

Ø  Data analysis and manipulation

AI Engineer or Machine Learning Engineer

Ø  Good understanding of cloud platforms and system architecture

Ø  Expertise in AI scalability and deployment

Ø  Knowledge of large-scale data pipelines

Ø  Experience on AI frameworks and libraries

Facts to Consider

Both these professions require some common skills, like advanced statistics, machine learning algorithms, programming efficiency in Python, R, etc., and understanding how to design infrastructure, yet there are some other skills that might help these professionals to gain a competitive advantage. Having those skills can give a good return on investment in the long run. Hence, whenever you are upskilling in the above-mentioned skills, it is recommended to pursue AI engineer certifications from globally accredited institutes to yield maximum benefits from the job market.

To help you out, search for institutes like United States Artificial Intelligence Institute, Massachusetts Institute of Technology (they offer professional certificates), NVIDIA, etc for building a successful AI career.

Additionally, it seems that AI developers will have more job prospects in the e-commerce, consumer goods, and business process automation sectors, which require embedding AI into applications. At the same time, it is easy to see the employment possibilities for AI engineers in the industries involving huge volumes and sophisticated AI models such as healthcare, self-driving cars and financial services requiring real-time processing and scaling of AI models.

Conclusion

The distinction between an AI engineer and an AI developer lies in their primary responsibilities. For example, AI developers work on designing and creating AI models with machine learning algorithms, whereas AI engineers work on implementing and deploying AI systems with skills like statistical analysis, data manipulation, etc. As AI continues to evolve, the demand for both engineers and developers will continue to rise; hence, with the best AI engineer certification, you can easily build a prosperous future!