Posted:1 day ago|
Platform:
On-site
Full Time
• You will develop, train, test and deploy machine learning models in various fields such as
computer vision, LLMs, tabular and time series data.
• Experimenting with novel deep learning based technologies such as self-supervised learning
and generative AI will also be part of your tasks
• You will support in setting up the MLOps infrastructure for existing and new AI products
• Additionally you will work directly with customer data and set up data pipelines to collect,
curate, transform and version data
You'll be working in the Artificial Intelligence team, AI global corporate division engaged with real business challenges and opportunities in multiple countries. Focus of this role is to support the AI team with extending existing and building new AI products for a vast amount of uses cases across
business and value chain. You'll collaborate across different business and corporate functions in international team composed of Project Managers, Data Scientists, Data and Software Engineers
in the AI team and others in the Global AI team.
As a Machine Learning Enginee, you will be working closely with our global AI team to create and
implement sustainable AI models, algorithms, and software solutions for our global industrial gases and engineering services operations. You will participate in the collection, analysis, interpretation, and output of large amounts of data using advanced AI techniques like deep learning, NLP, and computer vision.
• You have a Bachelor or Masters Degree in Data Science, Computational
Statistics/Mathematics, Computer Science or related field
• You know the basics of neural networks and have an initial practical experience with deep
learning frameworks like PyTorch and Tensorflow.
• You have experience in backend and API development with Python (FastAPI, Flask) or similar
• You demonstrate knowledge of and basic practical experience with Object Oriented
Programming, design patterns, algorithms and data structures, version control systems (e.g.
Git)
• Having basic experience with cloud platforms (e.g. Azure), Docker and Kubernetes is a plus
• Fluent English
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