Machine Learning Engineer II - Brackenfell at Shoprite Group of Companies

Job Objectives

• Liaise with stakeholders to analyze business problems, translate business requirements into conceptual and detailed system architecture and technology solutions. 
• Collaborate within a cross-functional team of Data Scientists, Engineers and Analysts in order to understand project goals, and build, implement and scale-up algorithms for measurable impact.
• Display basic understanding of 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.
• Work with above architectures within deep learning frameworks such as Keras and TensorFlow.
• Demonstrate end-to-end understanding of relevant applications and/or systems (including, but not limited to, the machine learning algorithms) being created.
• Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production.
• Use data modelling and evaluation strategy to find patterns and predict unseen instances.
• 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.
• Apply understanding of theoretical frameworks in computer science fundamentals, including data structures, algorithms, computability, complexity and computer architecture.
• Keep abreast of technological developments in the field, and integrate the latest data technologies into existing requirements.
• Follow best practices and standards of machine learning operations (MLOps) workflows for data preparation, deployment, monitoring and retraining to enable agile application methods to projects, and support machine learning models and data sets within a CI/CD process.

Qualifications

• Bachelor’s Degree in Data Science, Computer Science, Mathematics, Statistics, Information Technology, Information Systems or a related field – (essential). 
• Post Graduate Degree in the above or related fields – (desired).

Experience

• +3 years’ experience in a Machine Learning Engineer or similar role, applying complex mathematical and statistical concepts to build machine learning or deep learning models and/or systems - (essential). 
• In-depth experience with common machine learning, data, math and visualization libraries (i.e. Pandas, pyTorch, SciPy, NumPy, Scikit-Learn etc.) - (essential).
• Practical experience developing Machine Learning & NLP solutions over opensource platforms such as (TensorFlow, SparkML, OpenCV, pyTorch, etc.) - (essential).
• In-depth experience with different coding environments (local, notebooks, containers) and software engineering workflows (testing, code management/Git) - (essential).
• Experience delivering project outcomes using design thinking, lean and agile principles – (desired). 
• Experience in a retail, commercial or IT environment – (desired).