Descrizione dell'offerta
Are you passionate about technology, data and artificial intelligence? Do you like collaborating across teams to deliver success for customers bringing #EnergyForward? Join our Industrial & Energy Technology team, which provides industry‑leading products and services that promote the energy transition by improving the extraction, production, and processing of energy.
The Manufacturing Engineering Specialist – Testing Digital and Data Acquisition is responsible for the development, setup, maintenance, and applicability of the data acquisition system architecture in the testing areas of Florence, Massa and Avenza plants.
Responsibilities
Drive the digitalisation of test methodology with a strong focus on data analytics, machine learning and artificial intelligence, implementing related technologies and developing data acquisition and analysis software, primarily using Python. Design and set up the DAS (data acquisition systems), ensuring correct functionality of automatic measurement systems, software interfaces, calculation modules and data storage according to test specifications. Conduct turbomachine live data acquisition during test execution: data registration, quality control, corrective actions for calculation errors, post‑processing and advanced analysis using Python for live prediction of anomalies on the tested equipment leveraging machine‑learning models. Perform data post‑processing to detect hidden anomalies using AI and advanced analytics techniques, and generate documents and certificates for Baker Hughes customers, including automated reporting tools and data‑driven insights. Develop the DAS, including calculation and analysis software in Python, selection and verification of hardware measurement systems, definition of data acquisition practice, and development of machine‑learning algorithms for anomaly detection and predictive analysis. Develop and verify digital systems in the testing area, including network and system segregation, management systems, and servers, integrating AI‑driven solutions. Manage relationships and meetings with Engineering and Information Technology departments. Qualifications
Strong technical education; an engineering degree is preferred in automation, electronics, energy, telecommunication, informatics, or physics, with proven knowledge of turbomachine rotodynamics and thermodynamics. Holistic design mindset for solutions that involve hardware, software and network equipment. Strong programming skills and proven experience in developing software for data analysis, automation and industrial applications. Experience in machine learning and/or artificial intelligence applied to engineering or industrial data (e.g., anomaly detection, predictive maintenance, pattern recognition). Experience applying software and data‑driven solutions to machines and/or industrial plants, preferably in energy and/or manufacturing environments. Knowledge of data analysis algorithms, including manipulation of large data sets, waveform analysis, thermodynamic calculations and application of ML/AI techniques. Competence in computer programming using Python (mandatory) and other languages such as VB.NET, C#, Fortran, LabVIEW or PLC programming. Proven ability to understand technical drawings and specifications. Competence in the use of high‑precision measurement systems. Preferred knowledge of industrial communication protocols. At least two years of work experience as a software developer, data engineer, or system control designer, preferably in industrial or energy contexts. Excellent communication and presentation skills. Fluency in English and Italian and ability to work in the EU.
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Drive the digitalisation of test methodology with a strong focus on data analytics, machine learning and artificial intelligence, implementing related technologies and developing data acquisition and analysis software, primarily using Python. Design and set up the DAS (data acquisition systems), ensuring correct functionality of automatic measurement systems, software interfaces, calculation modules and data storage according to test specifications. Conduct turbomachine live data acquisition during test execution: data registration, quality control, corrective actions for calculation errors, post‑processing and advanced analysis using Python for live prediction of anomalies on the tested equipment leveraging machine‑learning models. Perform data post‑processing to detect hidden anomalies using AI and advanced analytics techniques, and generate documents and certificates for Baker Hughes customers, including automated reporting tools and data‑driven insights. Develop the DAS, including calculation and analysis software in Python, selection and verification of hardware measurement systems, definition of data acquisition practice, and development of machine‑learning algorithms for anomaly detection and predictive analysis. Develop and verify digital systems in the testing area, including network and system segregation, management systems, and servers, integrating AI‑driven solutions. Manage relationships and meetings with Engineering and Information Technology departments. Qualifications
Strong technical education; an engineering degree is preferred in automation, electronics, energy, telecommunication, informatics, or physics, with proven knowledge of turbomachine rotodynamics and thermodynamics. Holistic design mindset for solutions that involve hardware, software and network equipment. Strong programming skills and proven experience in developing software for data analysis, automation and industrial applications. Experience in machine learning and/or artificial intelligence applied to engineering or industrial data (e.g., anomaly detection, predictive maintenance, pattern recognition). Experience applying software and data‑driven solutions to machines and/or industrial plants, preferably in energy and/or manufacturing environments. Knowledge of data analysis algorithms, including manipulation of large data sets, waveform analysis, thermodynamic calculations and application of ML/AI techniques. Competence in computer programming using Python (mandatory) and other languages such as VB.NET, C#, Fortran, LabVIEW or PLC programming. Proven ability to understand technical drawings and specifications. Competence in the use of high‑precision measurement systems. Preferred knowledge of industrial communication protocols. At least two years of work experience as a software developer, data engineer, or system control designer, preferably in industrial or energy contexts. Excellent communication and presentation skills. Fluency in English and Italian and ability to work in the EU.
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