Description Client based in Sandton is hiring! We are in search of a Senior Machine Learning Operations Engineer (ML Ops Engineer) to join the Private Bank Technical Business Intelligence Team. The successful candidate will be responsible for deploying, maintaining, and monitoring machine learning models. We are looking for someone with a background in cloud infrastructure, Kubernetes, deployment pipelines, and a deep understanding of machine learning.
Responsibilities and skills include:Deliver strategic goals and business objectivesMaintaining platform stabilityDesign and build solutions focused on efficiencyStrong team dynamics, people skills and relationship/network buildingEnsuring the strategy and teamwork within the principles and practices of MLOps and engineering as defined by group engineering and best practicesSolid grasp of DevOps/SRE methodologies and practicesProvide technical guidance and support throughout the release process, including strong troubleshooting abilities across the platform and channelStrong design and solutioning experience, across multiple technologies and understanding of Cloud DevOps services and hostingGit and CI/CD understandingCloud native, hybrid cloud, and on-prem design principle understandingDeveloping and maintaining deployment pipelines for machine learning models on Microsoft AzureMonitoring and optimizing the performance of machine learning models in productionCollaborating with data scientists for seamless deployment of modelsEnsuring high availability and reliability of the machine learning infrastructure on Microsoft AzureProviding technical support for machine learning models in productionConducting regular security assessments and ensuring compliance with industry standards and best practicesKeeping up-to-date with new Azure ML offerings and technologies to continuously improve our ML ops processesRequirements:Minimum BSc Computer Science, Engineering, or related fieldAt least 5 years of experience in ML Operations or a similar roleExtensive experience with Microsoft Azure, Azure pipelines, Functions, and ML offeringsKnowledge of containerization technologies (Docker, Kubernetes, Rancher)Strong programming skills in Python, FastAPI, Redis, and SQLStrong understanding of Software Engineering conceptsStrong experience writing unit testsKnowledge of machine learning frameworks such as TensorFlow, PyTorch, etc.Experience with monitoring and logging tools (e.g. Grafana, Kibana, etc.)Excellent problem-solving skills and attention to detailKnowledge on design patterns
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