Stellenbeschreibung:

Location: Hybrid
Start: ASAP
Duration: 12 months renewable


Description:

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 productions 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 productions supervised and unsupervised ML models
• Work on data preprocessing, 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.

NOTE / HINWEIS:

EN: Please refer to Fuchsjobs for the source of your application

DE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung