At Air Products, we reimagine what’s possible. By tapping into the motivation of our people and our collective experience, we create the ideas and innovations that drive us forward. When we come together – where every voice is heard and everyone knows they belong and matter – we create solutions that launch people into space, support lifesaving care in hospitals, and enable the construction of groundbreaking, world scale production facilities.
Reimagine What’s Possible
POSITION SUMMARY
- The CO-OP will be part of a technology team for Air Products new technology center in Dhahran Techno Valley (DTV) in Saudi Arabia.
- The candidate will work on Data Science (DS), Machine Learning (ML) and Deep Learning (DL) techniques for applications in Chemical Engineering and/or Smart Sensors (Sound & Image processing).
- Primary focus will be on learning, writing python code and modules, and preparing best practices in applying AI algorithms (DS/ML/DL) for industrial applications.
- Understand and validate the underlying methods in Data Science/DL/ML algorithms and assess for use in the application.
- Troubleshoot problems in installation of firmware and setting up of a data pipeline.
- Test algorithms from developer communities and evaluate the new developments with available open-source code.
- Provide support in terms of recording and pre-processing field data (sound & image) and integration into application software.
- Apply Data Science/DL/ML/SP algorithms to field data, arrive at performance metrics and methods to improve performance.
- Document and present test cases and best practices.
- Familiarity with Numerical Methods or Deep Learning or Machine Learning or Data Science.
- Hands-on experience in coding in Python programming language is required, or alternatively, coding experience with C, C++, VBA or R.
- Previous experience of applying AI algorithms to any of data processing, sound or image processing, data fusion, software system integration.
Founded in 1940, Air Products is a world-leading industrial gases company and has a proud history of innovation, operational excellence, with an unwavering commitment to safety and environmental stewardship. Working together, we are taking our passion and diverse backgrounds forward to reimagine what’s possible and generate a cleaner future for our customers, our communities, and the world.
Skills Required
- Hands-on experience coding in Python
- Coding experience in C, C++, VBA or R
- Familiarity with Numerical Methods, Data Science, Machine Learning or Deep Learning
- Experience applying AI algorithms to data processing, sound or image processing, data fusion, or software system integration
- Ability to troubleshoot firmware installation and set up data pipelines
What We Do
Air Products (NYSE:APD) is a world-leading industrial gases company in operation for over 80 years focused on serving energy, environmental, and emerging markets. The Company has two growth pillars driven by sustainability. Air Products’ base business provides essential industrial gases, related equipment and applications expertise to customers in dozens of industries, including refining, chemicals, metals, electronics, manufacturing, and food. The Company also develops, engineers, builds, owns and operates some of the world's largest clean hydrogen projects supporting the transition to low- and zero-carbon energy in the heavy-duty transportation and industrial sectors. Additionally, Air Products is the world leader in the supply of liquefied natural gas process technology and equipment, and provides turbomachinery, membrane systems and cryogenic containers globally. The Company had fiscal 2023 sales of $12.6 billion from operations in approximately 50 countries and has a current market capitalization of about $65 billion. Approximately 23,000 passionate, talented and committed employees from diverse backgrounds are driven by Air Products’ higher purpose to create innovative solutions that benefit the environment, enhance sustainability and reimagine what's possible to address the challenges facing customers, communities, and the world.
