Machine Learning Engineer

2 giorni fa

Turin, Piemonte, Italia Aiko A tempo pieno
About the Role

We are seeking a highly skilled Machine Learning Engineer to join our team at Aiko, a cutting-edge deep-tech company specializing in developing advanced automation software for space missions. As a Machine Learning Engineer, you will play a crucial role in developing, implementing, and maintaining machine learning models to solve complex problems and drive innovation within our organization.

Key Responsibilities
  • Develop and deploy machine learning models for time series analysis and anomaly detection in space mission data.
  • Collaborate with the Machine Learning team to design and implement machine learning operations (MLOps) pipelines using industry-standard tools.
  • Work with the team to build and maintain a robust and efficient machine learning infrastructure.
  • Contribute to the development of new machine learning algorithms and techniques for space mission automation.
  • Deploy, manage, and optimize machine learning models in production environments, ensuring smooth integration and efficient operations.
Requirements
  • Master of Science in Computer Sciences, Engineering, Math, or a related field.
  • Demonstrated experience in Machine Learning and Deep Learning projects.
  • Strong statistical theoretical background.
  • Strong experience with Python 3 and libraries such as PyTorch, Tensorflow, MxNet, Pandas, Scikit-learn.
  • Strong mindset towards software quality.
Preferred Experience
  • Previous experience in Data Science, Artificial Intelligence, or related fields.
  • Previous experience in Data Analysis and time series analysis.
  • Expertise in designing and implementing MLOps pipelines using industry-standard tools.
What We Offer
  • A collaborative and inclusive work environment with a diverse and talented team.
  • Access to courses for skills improvement.
  • Flexible working hours and smart working policy (remote working available).
  • Ticket Restaurants and other benefits.
Interview Process

The interview process for this role will consist of two stages: an initial interview with our People & Talent and the Hiring Manager, followed by a technical step.

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