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1 week ago

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We’re looking for a Machine Learning Engineer who can take models from idea to production. This role is for someone who understands that model accuracy is only one part of the equation—scalability, reliability, and maintainability matter just as much.You’ll work closely with data scientists, software engineers, and product teams to build and deploy ML systems that create real business impact.What You’ll DoDesign, build, and deploy machine learning models into production systemsWork on data pipelines, feature engineering, and model training workflowsOptimise models for performance, scalability, and reliabilityIntegrate ML models with backend services and applicationsMonitor model performance and handle model drift and retrainingCollaborate with product teams to translate business problems into ML solutionsDocument models, assumptions, and system behaviour clearlyWhat We’re Looking ForStrong experience in machine learning and applied ML systemsHands-on expertise with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, or similar)Solid understanding of data structures, algorithms, and system designExperience working with large datasets and data pipelinesFamiliarity with model deployment, APIs, and production monitoringAbility to balance experimentation with engineering disciplineNice to Have (Not Mandatory)Experience with MLOps tools and workflowsExposure to cloud platforms (AWS, GCP, Azure)Experience with distributed training or large-scale inferenceBackground in NLP, computer vision, or recommendation systems

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