JUNIOR MACHINE LEARNING ENGINEER

  • R&D and Engineering
  • Italy
  • Cernusco Lombardone

Responsibilities:

The candidate will join the Industrial Automation department and will be responsible of:

  • Maintenance and development of AI&RPA models currently in production
  • Implementation of data management pipelines, including extraction and transformation of machine learning algorithms up to making available them for training
  • Monitoring of model performance metrics
  • Definition of technical requirements and pre-production tests in collaboration with SW/HW Development team
  • Effective communication of the results obtained, also directed to non-experts
  • Interaction with experts from the various Production Units and departments to identify opportunities for improvement related to the application of machine learning

Requirements:

We are currently on the lookout of candidates with the following characteristics:

  • Graduated or close to graduate, preferably in Data Science, Statistical Sciences, Big data Analytics, Applied Mathematics, Mathematical Engineering or related disciplines with excellent academic results
  • Knowledge of at least one of the following languages: Python, C ++, C #
  • Knowledge of machine learning frameworks (i.e.:Tensorflow, Keras, PyTorch)
  • Passion for data and bearer of a solid foundation in computer science
  • Superior skills in applying mathematical models to production
  • Good analytical skills and results oriented
  • Good interpersonal and communication skills
  • Proactive personality

Previous experience in the following areas is also considered:

  • Ability to use and manage relational databases (eg SQL server, MySQL) and noSQL
  • Big Data Analytics tools (eg. Hadoop, Spark)
  • Computer vision / image processing algorithms

Thesis works carried out in the field of machine learning will be considered a plus.

The profile of the candidate is completed by a strong ability to work in multidisciplinary and international teams, providing both creative and technical contribution. The best candidate is focused to production issues, product optimization, cost savings and process improvement.

A good knowledge of English and the availability for short trips in Italy and abroad are also required.

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