AI and Machine Learning Engineer (m/f/d) at CASE Deutschland GmbH
Deutschland, , Germany -
Full Time


Start Date

Immediate

Expiry Date

30 Jun, 25

Salary

0.0

Posted On

31 Mar, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Statistical Modeling, Computer Science, Computer Vision, Python, Software Engineering Practices, Reinforcement Learning, English, Natural Language Processing, Statistics, Mathematics

Industry

Information Technology/IT

Description

POSITION OVERVIEW:

We are looking for experienced AI and Machine Learning Engineers to join our team in Germany. In this role, you will design, develop, and deploy machine learning models and AI systems to support our products and services. The ideal candidate has strong technical skills, practical problem-solving abilities, and a commitment to advancing AI technologies.

REQUIRED QUALIFICATIONS & SKILLS:

  • Master’s degree or higher in Computer Science, Mathematics, Statistics, or a related field
  • Minimum 3 years of professional experience in AI/ML development
  • Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch, scikit-learn)
  • Experience with natural language processing, computer vision, or reinforcement learning
  • Solid understanding of machine learning algorithms and statistical modeling
  • Experience deploying ML models to production environments
  • Strong software engineering practices and knowledge of version control systems
  • Excellent problem-solving skills and attention to detail
  • Fluent in English; German language skills are a plus
Responsibilities
  • Design, develop, and optimize machine learning models and AI systems from conception to production
  • Implement and improve algorithms for data classification, prediction, and pattern recognition
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
  • Research and implement cutting-edge AI techniques to solve complex problems
  • Perform data preprocessing, feature engineering, and feature selection to prepare datasets for model training
  • Develop efficient code for data processing, model training, and inference pipelines
  • Evaluate and benchmark model performance, making continuous improvements
  • Create documentation and technical specifications for AI/ML systems
  • Monitor deployed models and implement strategies to ensure performance and reliability
  • Stay current with the latest advancements in artificial intelligence and machine learning
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