The Machine Learning Engineer is primarily responsible for building end-to-end machine learning models from ideation to deployment and scalability.
You would create new and improved datadriven solutions to assist the Group in answering business questions, gaining competitive advantage, identifying new market opportunities, increasing efficiencies, and / or reducing costs.
Work in a cross-functional team, collaborating with data scientists, engineers, and analysts to understand project goals, interpret end-users intent and drive the build, implementation and scale-up of algorithms for measurable impact
Understand and use ANN's, CNN's, RNN's, autoencoders, fundamental data science concepts (linear and logistic regression, SVM's, dimensionality reduction), decision trees, gradient boosting, ensemble models, etc.
to develop machine learning models
Implement above architectures with deep learning frameworks such as Keras and TensorFlow
Train models on large-scale data and fine tune hyper-parameters
Research and implement appropriate machine learning algorithms and tools by selecting the correct libraries, programming languages, and frameworks for each task
Understand and use computer science fundamentals, including data structures, algorithms, computability, complexity and computer architecture
Keep abreast of developments in the field and integrate the latest data technologies into existing requirements
Follow best practices and standards in machine learning
Peer review machine learning models, and advise on shortfalls and improvement
Provide guidance to junior machine learning engineers and the general team (where
Present complex machine learning concepts and results to both technical and non-technical audiences
Skills and Experience
4-year Degree / NQF level 7 in IT and Computer Sciences
EXPERIENCE : Essential :
At least 3 years of Machine Learning experience
At least 3 years of Data Science experience
KNOWLEDGE AND SKILLS :
Essential : Python
Probability and Statistics
Cloud Platform (AWS)