This role focuses on developing, optimizing, and deploying machine learning solutions, requiring strong technical skills in model development, pipeline management, and production integration. The position involves building and maintaining ML pipelines, collaborating with senior engineers, evaluating models, and staying current with industry trends.
The Intermediate Machine Learning Engineer is responsible for developing, optimizing, and deploying machine learning solutions that support data-driven decision-making and business objectives. The role requires strong technical expertise in model development , pipeline management , and integration within production environments.
Building and maintaining end-to-end machine learning pipelines for model development, training, testing, and deployment.Collaborating with Senior Engineers and Data Scientists to implement ML models into production environments. Conducting model evaluation and validation to ensure accuracy, scalability, and alignment with business goals.Documenting workflows, maintaining version control, and ensuring reproducibility of ML experiments.Keeping up-to-date with emerging tools, frameworks, and trends in machine learning and AI.NQF Level 6 or higher tertiary qualification in an ICT-related field, such as Information Systems, Computer Science, Data Science, Software Engineering. Preferred Certifications: Cloud platform certification with specialization in ML or AI services.Proven experience developing, deploying, and monitoring machine learning models in production.Experience with cloud-based ML services and tools .Strong programming skills in Python .Experience working with APIs and integrating ML models into production systems.Strong analytical, problem-solving, and debugging skills.
Machine Learning Model Development Pipeline Management Cloud Platforms Python
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