Machine Learning Scientist

Job Category: Machine Learning
Job Type: Full Time
Job Location: Pisa

Job description

We’re looking for enthusiastic and resourceful Machine Learning Scientists who are passionate about building ML models to improve our products, someone who loves being part of a team.

The ideal candidate will be responsible for developing, validate, and test ML models for the company. Using Python, TensorFlow or PyTorch this candidate will be able to translate user and business needs into ML models.


  • PhD degree in Machine Learning or equivalent practical experience
  • 3 years of experience in coding and scripting with Python, R, C++, or Java
  • Experience in Deep Learning
  • Experience with TensorFlow and/or PyTorch
  • Desire to work in a respectful, transparent, and collaborative work environment

Nice to have

  • 2+ years of experience applying ML in industry setting.
  • Publish research results in top-tier journals and at leading international conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP-IJCNLP
  • Experience in Natural Language Processing
  • Familiarity using Scrum/Agile development methodologies

What we offer

At Aptus.AI, we are proud of our talented team. We embrace change by providing a continuous learning environment for each team member and are passionate about trying out new technologies. We are a team that strives to make work an enjoyable and friendly experience in a relaxed atmosphere.

Aptus.AI purpose is to be a reference in talent and human quality, and we will only achieve it by being an open and diverse company, that is why we have a Code of Conduct that reflects or expectations of the people who participate in the company. We offer a friendly environment for everyone, regardless of their gender identity or expression, sexual orientation, ability, ethnicity, religion, socioeconomic status.


  • Competitive Salary
  • Startup Environment
  • Learning Budget
  • Flexible Working
  • Birthday Off
  • Team outings, including Paint Ball, Go-Kart and Escape Rooms
  • Peer-led learning sessions
  • Free beer

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