Administrative Positions
Full time
The AI Architect is responsible for providing architectural and technology leadership on the AI/ML front, and assist in leading university AI/ML initiatives.
Main roles & responsibilities

1. Architect, design, and lead the implementation of university AI/ML solutions.

2. Work with business units, to understand their processes, explore their data, identify their needs and use cases, and come up with relevant AI/ML solutions that give business value, present and sell the findings and recommendations, then implement the solutions

3. Apply research methodologies to identify the appropriate AI/ML architectures and models for the problem(s) at hand, and lead proof of concept implementations to ensure feasibility of identified solutions.

4. Monitor the effectivess of all implemented AI/ML solutions and recommend/implement the needed revisions to enhance their efficiencies and operations.

5. Manage teams, budgets, and projects, as needed, to deliver on assignments and initiatives.

6. Collaborate and work with other TD staff to ensure the timely, complete, and correct implementations fo all agreed solutions.

7. Look for opportunities to capitalize on technology advances through analysis of key industry and AI/ML trends to assess potential impact on the university.

8. Lead AI awareness efforts across the university including holding workshops and training, to both technical or semi/none-technical audiences.

Required qualification & skills
  • 5 years of direct work experience in architecting, building, and deploying AI/ML solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, {Deep} Neural Networks, Conditional Random Fields, Topic Modeling, Game Theory, etc.)

Education and Academic Qualifications:

  • Masters, PhD, or equivalent experience, in a quantitative field (applied mathematics, statistics, computer science, engineering, computational biology, artificial intelligence, etc.), from an accredited university.
  • Cloud certifications (preferably AWS) especially in the area of ML would be an advantage.

Knowledge, Skills & Abilities:

Must have (technical):

  • Experience architecting, designing, developing, training, evaluating, and deploying deep learning models using popular machine learning frameworks (such as PyTorch, TensorFlow, Keras, etc.).
  • Knowledge and application of state of art deep learning architectures (Resnet, Mobilenet, Xception, etc.).
  • Experience with AWS services related to the AI/ML ecosystem, particularly AWS Kinesis, AWS Lambda, SageMaker, Amazon DynamoDB, Elastic Search, Amazon S3, AWS Container Services like EKS, Fargate, etc.
  • Experience in software development in languages such as Python, Java, Scala, Spark, etc.
  • Experience with database scripting languages (such as SQL, PLSQL, TSQL, etc.)
  • Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.).

Other must have (soft) skills:

  • Strategic thinking
  • Critical thinking
  • Problem solving
  • Teamwork and collaboration
  • Communication and presentation (English language; Arabic language is an advantage)
  • Time management and organization
  • Adaptability and flexibility

Should have (technical):

  • Experience working with RESTful API and general service-oriented architectures.
  • Experience working with streaming and batch services, API development, NoSQL databases, and serverless technologies.
  • Strong hands-on experience ith statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.).
  • Experience in effective data exploration and visualization (e.g. Excel, Power BI, Tableau, etc.).
  • Experience working with DevOps tools to build CI/CD wpipelines and automation of cloud services deployment.