Lisbon ML Engineer: Build Scalable AI Solutions

FreshStart UAE

Lisboa

Presencial

EUR 8000 - 11 000

Tempo integral

14 dias+

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Resumo da oferta

FreshStart UAE in Lisbon is seeking a highly skilled Machine Learning Engineer to develop and implement machine learning models and algorithms to solve business problems. You will work closely with data scientists and software engineers to build and deploy scalable solutions.

Responsibilities include collecting and analyzing large datasets, designing ML solutions, and continuously evaluating model performance.

Qualificações

  • Bachelor's or Master’s degree in Computer Science, Data Science or related field.
  • Strong understanding of ML techniques such as regression, clustering, decision trees, etc.
  • Proficiency in Python, R, or Java.
  • Experience with TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with data visualization tools like Tableau or PowerBI.
  • Excellent problem-solving and communication skills; ability to work in a team.

Responsabilidades

  • Develop and implement machine learning algorithms.
  • Collect, clean and analyze large datasets to identify patterns.
  • Collaborate with cross-functional teams to meet business requirements.
  • Build scalable systems for data processing, model training and inference.
  • Continuously evaluate and improve model performance.
  • Stay up-to-date with latest ML techniques and tools.

Conhecimentos

ML techniques
Python/R/Java
Problem solving
Communication
Teamwork

Formação académica

Bachelor's or Master’s in CS/DS or related

Ferramentas

TensorFlow
PyTorch
scikit-learn
Tableau
PowerBI

Descrição da oferta de emprego

FreshStart UAE in Lisbon is seeking a highly skilled Machine Learning Engineer to develop and implement machine learning models and algorithms to solve business problems. You will work closely with data scientists and software engineers to build and deploy scalable solutions.

Responsibilities include collecting and analyzing large datasets, designing ML solutions, and continuously evaluating model performance.

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