Applied AI/ML Engineer

Position Summar:

KAUST is often approached by Saudi corporations and government agencies for assistance in solving technical challenges, for which artificial intelligence (AI) and machine learning (ML) methods are anticipated to be useful. The projects associated with these requests are often characterized by applied AI/ML activities, for which the measure of success is real-world impact for the associated client. To address this need, KAUST is establishing a new project-based unit that will employ AI/ML methods to address real-world problems presented by Saudi corporations and government entities.

As the projects addressed by the AI/ML engineers in this unit will be focused on important real-world applications, there is significant potential that the engineers involved may take the experience gained within the unit to subsequently constitute new startup companies. The spinning out of companies in this manner will be encouraged, with potential venture backing from KAUST and from the clients of this KAUST unit. Employment within this unit should be attractive to applied AI/ML engineers who may have the ultimate objective of launching a startup company in this space. However, it is not a requirement that individuals in this unit also start new companies in applied AI/ML.

Major Responsibilities:

An AI/ML engineer's primary responsibilities are the creation of AI/ML models and systems to solve real-world problems, and to maintain and retrain those systems when needed. If the AI/ML methodology needed to solve these challenges results in academic publications, that is a bonus, but the principal goal of these projects and of engineers working in this unit is to make business impact by applying AI/ML methodology to real-world problems.

The following is a non-exhaustive list of responsibilities.

• Designing AI/ML systems according to client requirements.
• Selecting appropriate data sets, verifying data quality, and picking appropriate data representation methods and storage formats.

• Researching and implementing AI/ML algorithms and tools.
• Transforming and converting AI/ML prototypes into production AI/ML applications.
• Running AI/ML system regression tests and using results to improve AI/ML systems.
• Training and retraining AI/ML systems as needed.
• Contributing to and extending open-source AI/ML libraries.

Engineers within this unit will also be able to engage with KAUST faculty in the field of AI/ML, to gain suggestions and leverage experience in problem solving.

Competencies:

• Successful engineers in this unit will be good at identifying the right methodology for a given problem, with a capacity to engage in data visualization and interpretation to make this identification.
• Good listening and interpersonal skills are also necessary, as regular communication is necessary with the client, often expected to be in the form of respectful back-and-forth discussions to get to the heart of the problem of interest. English language fluency is required.
• Engineers who fill this role will have knowledge and experience with the underlying methodology of machine learning and modern AI, as well as its implementation in software, using modern tools like Scikit-Learn, TensorFlow, and PyTorch.
• Engineers who fill this role will have knowledge and experience applying modern software engineering “best practices” including the use of Git/GitHub and CI/CD tools.
• Engineers who fill this role will have knowledge and experience coding and programming in languages such as Python, Java, C++, C, and JavaScript.
• Engineers in this unit will have experience in implementing AI/ML algorithms in software on modern computing platforms, including graphical processor units (GPUs).
• Experience with neural networks is expected, but knowledge and experience in other methodological areas of AI/ML is also sought.
• Experience in using AI/ML for time-series data analysis, image analysis and in solving differential equations are of interest.

Qualifications:

Must have at least an MS degree in computer science, math, statistics, or a related degree and have extensive experience (5+ years) in applying AI/ML methods to advanced, applied projects with real-world data.