Job Description

Job Details
Closing Date 2023/12/04
Reference Number SHO231127-2
Job Title Machine Learning Engineer II
Job Type Permanent
Location - Country South Africa
Location - Province Western Cape
Location - Town or City Brackenfell, Cape Town
Purpose of the Job

The purpose of the Machine Learning Engineer II is to apply in-depth computer science (including data structures, algorithms, computability and complexity) statistical modeling, and software engineering in machine learning operations (MLOps) to build cutting edge, end-to-end ML data models from ideation to deployment and scalability. The Machine Learning Engineer II is a core member of the data science and innovation team that supports the development of solutions to enable the Group increase efficiencies, reduce costs, identify opportunities that generate value and drive data as a competitive advantage. The role requires extensive experience in a range of software development and programming fields to design self-running software to automate predictive models while delivering features in a highly agile manner.

Job Advert Details
Job Category IT
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.

• Bachelorxe2x80x99s Degree in Data Science, Computer Science, Mathematics, Statistics, Information Technology, Information Systems or a related field xe2x80x93 (essential).

• Post Graduate Degree in the above or related fields xe2x80x93 (desired).

• +3 yearsxe2x80x99 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 xe2x80x93 (desired).

• Experience in a retail, commercial or IT environment xe2x80x93 (desired).

• Good proficiency in MS Office 365 and advanced Excel skills xe2x80x93 (essential).

• Understanding of Machine Learning Operations (MLOps) in the end-to-end machine learning development process to design and build reproducible, testable and evolvable machine learning solutions to meet business needs - (desirable).

• Knowledge of relational databases as SQL, MySQL - (essential).

• Practical knowledge and experience working in a cloud environment (AWS, Azure, GCP) and containerized environment (Mesos, Kubernetes, Docker) and CI/CD (Jenkins, AWS Code Pipelines) - (desirable).

Shoprite Holdings