
Machine Learning Operations Engineer
- Sandton, Johannesburg
- Permanent
- Full-time
- Deliver strategic goals and business objectives
- Maintaining platform stability
- Design and build solutions focused on efficiency
- Strong team dynamics, people skills and relationship/network building
- Ensuring the strategy and teamwork within the principles and practices of MLOps and engineering as defined by group engineering and best practices
- Solid grasp of DevOps/SRE methodologies and practices
- Provide technical guidance and support throughout the release process, including strong troubleshooting abilities across the platform and channel
- Strong design and solutioning experience, across multiple technologies and understanding of Cloud DevOps services and hosting
- Git and CI/CD understanding
- Cloud native, hybrid cloud, and on-prem design principle understanding
- Developing and maintaining deployment pipelines for machine learning models on Microsoft Azure
- Monitoring and optimizing the performance of machine learning models in production
- Collaborating with data scientists for seamless deployment of models
- Ensuring high availability and reliability of the machine learning infrastructure on Microsoft Azure
- Providing technical support for machine learning models in production
- Conducting regular security assessments and ensuring compliance with industry standards and best practices
- Keeping up-to-date with new Azure ML offerings and technologies to continuously improve our ML ops processes
- Minimum BSc Computer Science, Engineering, or related field
- At least 5 years of experience in ML Operations or a similar role
- Extensive experience with Microsoft Azure, Azure pipelines, Functions, and ML offerings
- Knowledge of containerization technologies (Docker, Kubernetes, Rancher)
- Strong programming skills in Python, FastAPI, Redis, and SQL
- Strong understanding of Software Engineering concepts
- Strong experience writing unit tests
- Knowledge 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 detail
- Knowledge on design patterns
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