Key responsibilities:
– Develop innovative solutions in AI and remain well-versed in new technologies in the evolving AI space;
– Supervise/mentor junior staff in the area(s) of expertise;
– Generate and contribute towards science engineering and technology (SET) activity outputs e.g., reports, guidelines, system requirements, peer-reviewed publications, and technology and software packages;
– Understand and interpret client requirements by contributing to user requirement analysis and/or well-articulated proposals;
– Remain current in field of expertise with respect to new approaches in tools, methods or technologies;
– Participate in external task teams or committees in relevant domains;
Qualifications, skills and experience:
– A Bachelor’s degree in computer science/engineering, electrical/electronic engineering, information technology or related field with at least three years’ experience in Artificial Intelligence/Machine Learning (ML) and software development in Artificial Intelligence Technologies;
– An Honours or Master’s degree will be advantageous;
– Experience in the following:
o Applied machine-learning with regression, classification, etc. models for supervised learning;
o Big-data unsupervised learning;
o Data platform engineering;
o Building AI models with a deep learning framework such as TensorFlow, Keras or Theano;
o Bringing theoretical machine-learning approaches illustrated in academia research papers to actual implementations, i.e. implemented and deployed into large-scale production system certain advanced ML and applied ML algorithms;
- The following knowledge will be advantageous:
o Cloud-based platforms: AWS, IBM Cloud, Azure;
o Understanding of transforming/implementing software/algorithms for use in real-life systems; - Must be able to:
o Select hardware to run an ML model with the required latency;
o Supervise/mentor/develop junior staff; - Must have knowledge and/or experience of object-orientated software engineering;
- Demonstrated skills in: analytical thinking, flexibility and adaptability, investigative orientation, planning and organising, problem solving, verbal and written communication, teamwork, selfmanagement (planning, prioritising and time management – includes the ability to work independently), systems level thinking, multi-disciplinary knowledge.
- Strong quantitative skills (mathematics/statistics/computer science);
- All international qualifications require an evaluation report / certificate issued by the South African Qualifications Authority (SAQA).
Desired Skills:
- Analytical thinker
Desired Qualification Level:
- Degree