Job Description
The Specialist Machine Learning Engineer is responsible for advancing the organisations technical capabilities in specific, high-impact areas of machine learning such as natural language processing (NLP), computer vision, or reinforcement learning. This role combines deep research expertise with practical engineering skills to design, prototype, and deploy innovative ML solutions that address complex, domain-specific business challenges. The incumbent serves as a subject-matter expert and innovation driver, ensuring that the organisation remains at the forefront of emerging ML technologies and methodologies.
Key Responsibilities:
- Focus on niche areas of machine learning, such as NLP, computer vision, or reinforcement learning, to deliver specialised solutions.
- Develop and refine domain-specific ML models tailored to unique business needs, leveraging advanced algorithms and architectures.
- Conduct in-depth research, feasibility studies, and prototyping of innovative ML approaches using cutting-edge methods and tools.
- Identify opportunities to apply the latest advancements in machine learning to enhance processes, improve decision-making, or create new business capabilities.
- Work closely with other ML Engineers, Data Scientists, and Software Engineers to transfer research insights into scalable, production-ready solutions.
- Provide expert-level insights on specific ML tools, frameworks, or algorithms, guiding the organisation in adopting best-in-class technologies.
- Contribute to the design and development of internal ML tools, utilities, and libraries to streamline experimentation, model management, and deployment workflows.
Requirements
- NQF Level 6 or higher tertiary qualification in an Information and Communication Technology (ICT) field (e.g., Computer Science, Information Systems, Data Science, or related discipline).
- Cloud certification (AWS, Azure, or GCP) preferred.
- Minimum of 6 years experience in a Machine Learning Engineer or related advanced AI/ML role.
- Proven expertise in one or more ML specialisations (e.g., NLP, computer vision, or reinforcement learning).
- Strong background in research, experimentation, and model deployment.
- Demonstrated ability to translate research into practical, high-performance production systems.
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