Machine Learning Engineer

Job description

Job description:

Purpose Statement
  • To build, implement, improve and support the AI platform which will support delivery of the Capitec AI strategy.
  • To collaborate in creating and delivering the AI strategy to ensure Capitec is able to compete in a fast changing landscape.  The effective use of AI technologies will be a key strategic differentiator in the future.

Proven experience in:

  • 2+ yrs software development experience
  • Strong analytical and problem-solving skills
  • Expert in Python and SQL
  • Experience with the modern software development best practices, e.g.
    • agile software development
    • code reviews
    • unit testing
    • version control, e.g. git
    • CI/CD
  • Experience with microservice architectures
  • Experience working in an agile team
  • Experience with ML frameworks and tools (e.g. pandas, numpy, scikit-learn, TensorFlow, Pytorch, Spark MLlib)
  • Experience with modern ETL, compute and orchestration frameworks, e.g. Apache Spark, Apache Flink, Apache Kafka, etc.
  • Development experience in both Windows and Linux
  • Experience with container technologies, e.g. Docker, Kubernetes


  • Experience in building machine learning or AI systems
  • Proficiency in R language
  • Experience deploying models to production
  • Experience building distributed systems
  • Experience with NoSQL databases
  • Experience working with ML platforms, e.g. MLflow, Kubeflow, etc.
  • Experience working with Data Science platforms, e.g. Dataiku, Domino, etc.
  • Experience with cloud-based infrastructure, e.g. Azure, AWS, GCP; ideally AWS
Qualifications (Minimum)
  • A relevant qualification in Information Technology - Computer Science or Engineering - Other
Qualifications (Ideal or Preferred)
  • Masters Degree in Information Technology - Computer Science or Engineering - Other

Must have knowledge of:

  • Object oriented and functional programming in Python
  • Modern software development practices
  • Database querying using SQL
  • Data life cycle
  • Machine learning concepts
  • Machine learning model life cycle
  • Microservice architectures

Knowledge of:

  • Data Science lifecycle
  • Distributed system design
  • Big data storage and processing solutions
  • Machine learning model architectures
  • Analytical Skills
  • Decision making skills
  • Planning, organising and coordination skills
  • Problem solving skills
  • Researching skills
Conditions of Employment
  • Clear criminal and credit record
  • A valid driver's license and own vehicle is required
  • Contactable via own mobile phone

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