Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
About the role
- Machine Learning Engineer leveraging advanced AI techniques for defense technology solutions. Collaborating with cross-functional teams to innovate and implement AI-driven models.
Responsibilities
- conduct statistical analyses on business processes using ML techniques
- train, test, deploy, and maintain models that learn from data
- own and define the direction of mission-critical solutions by implementing AI
- guide clients as they navigate the landscape of ML algorithms, tools, and frameworks
- collaborate with data engineers, data scientists, solutions architects, and product owners
Requirements
- 5+ years of experience with artificial intelligence, data science, or machine learning engineering
- 3+ years of experience with Python coding and libraries, including scikit-learn, TensorFlow, or PyTorch
- Experience with developing code using a common programming language, including Python, C++, Rust, or Java
- Experience with deep learning, computer vision, or generative AI
- Experience with supervised and unsupervised learning
- Experience with data handling and model development
- Ability to solve client issues and problems
- Secret clearance
- Bachelor's degree
Benefits
- health, life, disability, financial, and retirement benefits
- paid leave
- professional development
- tuition assistance
- work-life programs
- dependent care
- recognition awards program
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