Senior Machine Learning Engineer

Cape Town - South Africa

Monthly Salary: Not Disclosed

Experience Required: 5years

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

The Senior Machine Learning Engineer is responsible for designing developing and deploying advanced machine learning solutions that drive business impact. This role requires deep technical expertise strong problem-solving skills and the ability to lead complex projects from conception through to production. The incumbent will play a key role in shaping the organisations ML strategy mentoring junior engineers and ensuring scalable efficient and ethical use of AI technologies.

Key Responsibilities:

Design and implement advanced machine learning models and systems to solve complex business challenges.
Lead the end-to-end lifecycle of ML projects including data preparation model training validation deployment and ongoing monitoring.
Optimise existing ML models and pipelines for scalability efficiency and performance in production environments.
Partner with data engineers software developers and business stakeholders to integrate ML solutions seamlessly into existing systems and workflows.
Provide mentorship guidance and technical leadership to mid-level and junior ML engineers to ensure knowledge sharing and adherence to best practices.
Develop maintain and enforce standards for model governance documentation versioning and reproducibility.
Stay abreast of emerging trends tools and technologies in machine learning MLOps and AI ethics to continually improve solutions and frameworks.

Requirements

NQF Level 6 or higher tertiary qualification in an ICT-related field (e.g. Computer Science Information Systems Data Science or related discipline).
Cloud certification (e.g. AWS Azure or GCP) preferred.
Minimum of 5 years experience in a Machine Learning Engineer or similar role.
Proven track record of designing developing and deploying ML models in production environments.
Experience with modern ML frameworks and libraries (e.g. TensorFlow PyTorch Scikit-learn).
Solid understanding of data engineering model lifecycle management and MLOps practices.

Required Skills:

Machine Learning Cloud Python ML Frameworks API Integration ML Development

Key Responsibilities:

Design and implement advanced machine learning models and systems to solve complex business challenges.
Lead the end-to-end lifecycle of ML projects including data preparation model training validation deployment and ongoing monitoring.
Optimise existing ML models and pipelines for scalability efficiency and performance in production environments.
Partner with data engineers software developers and business stakeholders to integrate ML solutions seamlessly into existing systems and workflows.
Provide mentorship guidance and technical leadership to mid-level and junior ML engineers to ensure knowledge sharing and adherence to best practices.
Develop maintain and enforce standards for model governance documentation versioning and reproducibility.
Stay abreast of emerging trends tools and technologies in machine learning MLOps and AI ethics to continually improve solutions and frameworks.

Requirements

NQF Level 6 or higher tertiary qualification in an ICT-related field (e.g. Computer Science Information Systems Data Science or related discipline).
Cloud certification (e.g. AWS Azure or GCP) preferred.
Minimum of 5 years experience in a Machine Learning Engineer or similar role.
Proven track record of designing developing and deploying ML models in production environments.
Experience with modern ML frameworks and libraries (e.g. TensorFlow PyTorch Scikit-learn).
Solid understanding of data engineering model lifecycle management and MLOps practices.