Description:
- 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 domain
Requirements:
- 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 domain
- A Bachelor’s degree in computer science/engineering, electrical/electronic engineering, information technology
- An Honours or Master’s degree will be advantageous
- 5 years’ experience in Artificial Intelligence/Machine Learning and software development in Artificial Intelligence Technologies
- Applied machine-learning with regression, classification, etc. models for supervised learning
- Natural language processing and understanding
- Large language models
- Building multimodal models
- Unstructured data
- Big-data unsupervised learning
- Data platform engineering
Demonstrated experience in bringing theoretical machine-learning poaches - Data platform engineering
- Demonstrated experience in bringing theoretical machine-learning approaches.
- illustrated in academia research papers to actual implementations, i.e. implemented ML algorithms
- Cloud-basedplatforms:AWS,IBMCloud,Azure
- Proficiency and experience building AI models with a deep learning framework such as TensorFlow, Keras or Theano
- Ability to select hardware to run an ML model with the required latency as TensorFlow, Keras or Theano
- Ability to select hardware to run an ML model with the required latency
- Exposure to Project Management
- Understanding of transforming/implementing software/algorithms for use in real-life systems would be advantageous
- Knowledge of programming in modern object orientated languages, with Open-Source development tools and platforms
- Ability to demonstrate Object-orientated software engineering skills
- Strong quantitative skills (mathematics/statistics/computer science)
- Demonstrated ability to supervise/mentor/develop junior staff
- Demonstrated skills in: analytical thinking, flexibility and adaptability, investigative orientation, planning and organising, problem solving, verbal and written communication, teamwork, self- management (planning, prioritising and time management – includes the ability to work independently), systems level thinking, multi-disciplinary knowledge.
- All international qualifications require an evaluation report / certificate issued by the South African Qualifications Authority (SAQA).
Qualifications
- A Bachelor’s degree in computer science/engineering, electrical/electronic engineering, information technology
- An Honours or Master’s degree will be advantageous
Experience
- 5 years’ experience in Artificial Intelligence/Machine Learning and software development in Artificial Intelligence Technologies
- Applied machine-learning with regression, classification, etc. models for supervised learning
- Natural language processing and understanding
- Large language models
- Building multimodal models
- Unstructured data
- Big-data unsupervised learning
- Data platform engineering
Demonstrated experience in bringing theoretical machine-learning poaches - Data platform engineering
- Demonstrated experience in bringing theoretical machine-learning approaches.
- illustrated in academia research papers to actual implementations, i.e. implemented ML algorithms
- Cloud-basedplatforms:AWS,IBMCloud,Azure
- Proficiency and experience building AI models with a deep learning framework such as TensorFlow, Keras or Theano
Skills and Knowledge
- Ability to select hardware to run an ML model with the required latency as TensorFlow, Keras or Theano
- Ability to select hardware to run an ML model with the required latency
- Exposure to Project Management
- Understanding of transforming/implementing software/algorithms for use in real-life systems would be advantageous
- Knowledge of programming in modern object orientated languages, with Open-Source development tools and platforms
- Ability to demonstrate Object-orientated software engineering skills
- Strong quantitative skills (mathematics/statistics/computer science)
- Demonstrated ability to supervise/mentor/develop junior staff
- Demonstrated skills in: analytical thinking, flexibility and adaptability, investigative orientation, planning and organising, problem solving, verbal and written communication, teamwork, self- management (planning, prioritising and time management – includes the ability to work independently), systems level thinking, multi-disciplinary knowledge.
- All international qualifications require an evaluation report / certificate issued by the South African Qualifications Authority (SAQA).
30 Apr 2024;
from:
careers24.com