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Technical production lead

Düsseldorf
Masentó Group
Produktioner
Inserat online seit: 2 Juni
Beschreibung

Lead Artificial Intelligence Engineer - Dusseldorf
Masentó are supporting an innovative and scaling Energy & Utilities manufacturing company based in Dusseldorf, Germany.
We're actively looking to speak with highly-skilled AI Engineer, who can take charge of a high-performing team.

Key Responsibilities
Design and build scalable machine learning models and AI systems for applications such as demand forecasting, predictive maintenance, asset optimization, and energy usage analytics.
Lead the end-to-end development lifecycle of AI solutions—from data exploration and feature engineering to model training, validation, deployment, and monitoring.
Collaborate closely with data engineers, software developers, domain experts, and business stakeholders to deliver impactful AI products.
Ensure AI solutions are secure, ethical, and comply with regulatory and privacy requirements.
Provide technical mentorship to junior engineers and data scientists within the team.
Stay up to date on the latest AI technologies, tools, frameworks, and trends, and evaluate their applicability to the organization’s needs.

Key Requirements & Experience
~ Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related technical field (Ph.D. is a plus).
~5–8 years of experience in machine learning or AI engineering roles, preferably in an energy, utilities, or industrial setting.
~ Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost).
~ Experience with time-series forecasting, anomaly detection, optimization, or reinforcement learning.
~ Deep understanding of MLOps practices and tools (e.g., MLflow, Kubeflow, Docker, Git, CI/CD pipelines).
~ Familiarity with energy systems and operational data sources (e.g., SCADA, AMI, GIS) is a strong plus.
~ Experience deploying models in production environments using cloud services (Azure, AWS, or GCP).
~ Ability to explain complex technical concepts to non-technical stakeholders.

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