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Senior Machine Learning Engineer

Sii tra i primi a mandare la candidatura.
ShopriteX
Wes-Kaap
ZAR 600.000 - 900.000
Sii tra i primi a mandare la candidatura.
4 giorni fa
Descrizione del lavoro

Value Proposition

The Shoprite Group is Africa’s largest fast-moving consumer goods retailer with over 35 million customers and 2,500 outlets. Our customers are at the heart of what we do, and our sole purpose is to provide all communities with high quality products at the most affordable prices. Within such a dynamic environment, innovation and the effective application of technology are becoming essential to maintain a competitive position. We continue to invest in being a technologically innovative and enabled business. You will be part of delivering complex machine learning and data solutions to some of the most recognised retail brands in South Africa. You will be surrounded by teams and individuals who challenge you and inspire you to be extraordinary. Are you ready to make an impact?

Role Purpose

The purpose of the Senior Machine Learning Engineer 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.

Role Description

  • Liaise with stakeholders to analyse 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 and Experience

  • 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).
  • +4 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 visualisation 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).
  • Familiarity with Code Repository Management, API Integration, and RAG (Red, Amber, Green) status reporting – (essential).
  • Experience with deep learning techniques, Generative AI, Generative Learning – (essential).
  • In-depth experience with different coding environments (local, notebooks, containers) and software engineering workflows (testing, code management/Git) - (essential).
  • Practical experience with programming languages including Python, R – (essential).
  • Experience working with large datasets – (essential).
  • Good proficiency in MS Office 365 and advanced Excel skills – (essential).
  • Advanced 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 - (essential).
  • Knowledge of relational databases as SQL, MySQL - (essential).
  • Practical knowledge and experience working in a cloud environment (AWS, Azure, GCP) and containerised environment (Mesos, Kubernetes, Docker) and CI/CD (Jenkins, AWS Code Pipelines) - (desirable).
  • Experience delivering project outcomes using design thinking, lean and agile principles – (desired).
  • Experience in a retail, commercial or IT environment – (desired).

Our Group and all its operating companies is committed to creating, embracing, and preserving a diverse workplace that values the unique talents, perspectives, backgrounds, and abilities that enrich our organisation. A place where everyone matters and feels included.

We are committed to Employment Equity when recruiting internally and externally.

Please take note that by responding to this application and providing your personal information, you confirm your express and informed consent for Shoprite Checkers (Pty) Ltd and all its subsidiaries and affiliates companies to process your personal information for the Company to consider your application for this position. All Personal Information which you provide to the Company will be used and/or retained only for the purposes for which it is collected, whereafter it will be permanently destroyed. Your information is only retained if it is required by law or where you have given consent to us to retain such information for an extended period.

If you don’t hear from us within 14 days, please consider your application unsuccessful. Any personal information collected as part of your application will be destroyed, securely, in accordance with South African legislation.

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* Il benchmark retributivo si basa sugli obiettivi retributivi dei leader del mercato nei rispettivi settori. È pensato per orientare gli utenti Premium nella valutazione delle posizioni aperte e aiutarli a negoziare la propria retribuzione. Tale benchmark non è fornito direttamente dall'azienda, quindi la retribuzione effettiva potrà risultare anche notevolmente superiore o inferiore.

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