Machine Learning Engineer

XpertDirect; München; Vor Ort; EUR 65.000 - 90.000; Vollzeit

Zusammenfassung

XpertDirect is seeking a Machine Learning Engineer in Munich to develop and productionise ML models for forecasting, anomaly detection, and operational optimisation. You will work across the ML lifecycle—from data exploration and model development through deployment and production improvement.

You will build models with Python and PyTorch, deploy on AWS, containerise workloads with Docker, and collaborate across Data, Software and Product teams to turn real-world problems into scalable ML

Qualifikationen

• 3+ years in Machine Learning Engineering, Applied ML, Data Science with production experience.
• Experience taking ML models from experimentation into production.

Aufgaben

• Develop and train ML models using Python and PyTorch.
• Build forecasting and anomaly-detection solutions.
• Develop models for operational and process optimisation.
• Explore and prepare structured and time-series datasets.
• Build feature-engineering and data-processing workflows.
• Evaluate models using appropriate metrics and experimentation.
• Productionise models and integrate them into software applications.
• Track experiments and model versions using MLflow.
• Containerise ML workloads using Docker.
• Deploy and operate ML services on AWS.
• Monitor production model behaviour and improve performance over time.
• Collaborate with Data, Software, and Product teams to turn operational problems into ML solutions.

Kenntnisse

Machine Learning Engineering

Production experience

Tools

PyTorch

Docker

AWS

MLflow

FastAPI

Airflow

XGBoost

LightGBM

Jobbeschreibung

Our client, a growing Industrial AI company based in Munich, is looking for a Machine Learning Engineer to develop and productionise ML models for forecasting, anomaly detection, and operational optimisation.

You’ll work across the ML lifecycle—from data exploration and model development through deployment and production improvement—on AI systems designed to solve real industrial challenges.

What You’ll Work On

• Develop and train machine-learning models using Python and PyTorch
• Build forecasting and anomaly-detection solutions
• Develop models for operational and process optimisation
• Explore and prepare structured and time-series datasets
• Build feature-engineering and data-processing workflows
• Evaluate models using appropriate metrics and experimentation
• Productionise models and integrate them into software applications
• Track experiments and model versions using MLflow
• Containerise ML workloads using Docker
• Deploy and operate ML services on AWS
• Monitor production model behaviour and improve performance over time
• Collaborate with Data, Software, and Product teams to turn operational problems into ML solutions

Core Skills

• 3+ years in Machine Learning Engineering, Applied ML, Data Science with production experience, or a similar role
• Experience taking ML models from experimentation into production

Nice to Have

• Forecasting
• Anomaly detection
• XGBoost / LightGBM
• FastAPI
• Airflow
• IoT or sensor data
• Manufacturing or industrial systems experience