IT Application Solutions

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Overview 综述:

Celanese Corporation is a global chemical leader in the production of differentiated chemistry solutions and specialty materials used in most major industries and consumer applications. Our businesses use the full breadth of Celanese's global chemistry, technology and commercial expertise to create value for our customers, employees, shareholders and the corporation. As we partner with our customers to solve their most critical business needs, we strive to make a positive impact on our communities and the world through The Celanese Foundation. Based in Dallas, Celanese employs approximately 13,000 employees worldwide and had 2023 net sales of $10.9 billion. For more information about Celanese Corporation and its product offerings, visit

Responsibilities 职责:

Key Responsibilities:  


 Document best practices of ML to be followed by the IT Development and 
Business teams for indefectible ML systems and for the efficient flow of 
 Identify challenges faced by data analysts and data scientists and develop 
solutions to integrate into the existing platform. 

 Possess good problem-solving skills and knowledge of machine learning 
techniques for solving a range of problems. 
 Possess knowledge of neural network programs and natural language 
 Write programs and algorithms to extract insights from large data sets. 

Qualifications 要求:

 6+ years of experience as Machine Learning Engineer with Optical 
character recognition. 
 Proficient in contextualizing PDF documents with Enterprise systems like 
SAP, TrackSys, Aveva PI etc. 
 Implement AI and ML solutions and establish system operations and 
maintenance structures. 
 Provide strategic and operational advice to the stakeholders regarding 
AI/ML infrastructure to serve current and future needs. 
 Transform data science prototypes and optimise machine learning 
solutions for scalability and deployment into production. 
 Design dynamic ML models and systems which have the ability to train, 
retrain, and untrain themselves whenever required. 
 Periodically evaluate the ML systems and ensure that end solutions are in 
alignment with corporate and IT strategies. 
 Evaluate the variations in data distribution that affects the model 
 Visualise data for insights and perform statistical analysis, applying new 
insights to improve the model. 

Apply 申请:

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