Machine Learning Engineer

Location: Hybrid

Start: ASAP

Duration: 12 months renewable

Design and deploy high-impact ML systems across real-world industries

We’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 models
• Work on data pre-processing, feature engineering and transformation pipelines
• Deploy models into cloud-native environments (AWS/GCP/Azure)
• Monitor performance and retrain based on drift or feedback loops

Key Skills & Competencies:

• 4+ years experience building and deploying ML systems in production
• Solid Python skills and experience with frameworks like Scikit-Learn, PyTorch, TensorFlow
• Familiarity with ML lifecycle tools: MLflow, Airflow, SageMaker, VertexAI
• Understanding of performance monitoring, A/B testing, and bias mitigation

If you love making AI useful – not theoretical – this is the gig for you.