Machine Learning Engineer

Location: HybridStart: ASAPDuration: 12 months renewableDesign and deploy high-impact ML systems across real-world industriesWe’re partnering with a fast-scaling data consultancy delivering applied machine learning solutions for financial services, SaaS and smart logistics. We’re hiring a Machine Learning Engineer to design and productionise models that improve decision-making, automation and customer engagement. You’ll work closely with Data Engineers, Analysts, and Product Owners to build end-to-end pipelines that deliver measurable outcomes. From experimentation to deployment, you’ll own your models. Key Responsibilities:

Train, evaluate and productionise supervised and unsupervised ML modelsWork on data pre-processing, feature engineering and transformation pipelinesDeploy models into cloud-native environments (AWS/GCP/Azure)Monitor performance and retrain based on drift or feedback loopsKey Skills & Competencies: 4+ years experience building and deploying ML systems in productionSolid Python skills and experience with frameworks like Scikit-Learn, PyTorch, TensorFlowFamiliarity with ML lifecycle tools: MLflow, Airflow, SageMaker, VertexAIUnderstanding of performance monitoring, A/B testing, and bias mitigationIf you love making AI useful – not theoretical – this is the gig for you.