Machine Learning Engineer and Data scientist
SATE Systems and Advanced Technologies Engineering Machine Learning Engineer and Data scientist
Summary
ML engineer/data scientist at SATE joining a multi-disciplinary team building AI- and model-based software for systems health monitoring, diagnostics and data mining in space and automotive applications. Day-to-day work centres on time-series analysis, signal processing and ML/deep learning modelling with Python, MATLAB/Simulink, C++/Java.
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Master’s degree in Computer Science, Data Science, Physics, Mathematics, or related Engineering fields with up to 5 years of experience.
Activity
You will be part of a multi-disciplinary team that implements innovative AI-based and model-based software solutions for systems health monitoring, diagnostics and data mining for space and/or automotive applications. You will be supported by our team leaders in a professional growth and training path that will gradually lead you to autonomy in data analysis activities and development of models, methods and software solutions.
Requirements
- Excellent knowledge of advanced techniques of timeseries data analysis and modelling, including signal processing, feature extraction, Machine Learning and Deep learning applied to timeseries.
- Excellent knowledge of programming in high-level languages (e.g. MATLAB / SIMULINK, Python, C ++, Java);
- Knowledge of data mining and data cleaning techniques.
- Knowledge of the English language (read, written and spoken); at least level B2 (CEFR) is required
- Advanced knowledge of the Microsoft Office environment, in particular Word and Excel. xysqume
What we offer
- Hiring contract framed according to CCNL trade sector SME.
- Hybrid remote working options (combination of in-office and work from home)
- Opportunity to work with cutting-edge technologies, innovative technology projects and software tools development
- Possibility to be involved in different projects and different fields
- On-the-job training
- Direct contact with innovation centers of clients and partners
- Opportunities to grow in role and responsibilities
- Company benefits like flexible hours, meal vouchers, online or in-company learning courses, periodical showcases and knowledge sharing sessions, common break/snack room
- Salary and additional benefit/bonus commensurate with experience, autonomy and objectives achieved
Work Schedule
Full time, Monday through Friday, flexible hours.
