über Arbeitnehmerüberlassung: Machine Learning Engineer - Agricultural Applications (m/w/d)

Overview

The European Technology Innovation Center (ETIC) of John Deere is part of a global R&D network in Kaiserslautern. Its focus is on the research on and development of future trends and technologies in the area of mobile agricultural and construction machines in close collaboration with diverse research institutes.

The John Deere Intelligent Solutions Group in Kaiserslautern is offering a contingent/leasing position ("Arbeitnehmerüberlassung") for a Machine Learning Engineer – Agricultural Applications (m/w/d) .

We are seeking a passionate and innovative Machine Learning Engineer to join our Precision Tech Automation & Sensing team. In this role, you will design, develop, and deploy machine learning models that revolutionize agricultural operations—from real-time sensing to perception-based automation that make John Deere equipment easier to operate and more productive in the field.

You’ll work alongside agronomists, data scientists, and software engineers to bring intelligent solutions to the field, leveraging one of the world’s richest agricultural data ecosystems.

What you can look forward to:

• Attractive compensation package
• Hybrid work in a 35-hour workweek
• Excellent social benefits
• Flexible and modern working environment, as well as development and training opportunities
• Work-life balance with a variety of family-friendly offerings

These are your responsibilities:

• Develop and deploy ML models for applications such as plant identification, crop classification, and material properties.
• Collaborate with cross-functional teams to integrate ML solutions into agricultural machinery.
• Analyze large-scale agronomic and machine datasets to extract actionable insights.
• Contribute to the design of data pipelines and MLOps infrastructure for scalable model deployment.
• Participate in field trials and validation of ML-driven features in real-world agricultural environments.

You bring:

• Master's in Computer Science or related field
• Strong foundation in machine learning principles
• Proficiency in Python and ML frameworks
• Experience with data preprocessing and analysis
• Effective cross-functional collaboration skills
• Curiosity and adaptability in dynamic environments

How to apply

If you see yourself in this description, we look forward to receiving your online application through our applicant portal!

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