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Machine Learning Engineer

A machine learning engineer is responsible for designing and implementing machine learning models and algorithms to solve complex business problems. They work closely with data scientists and software engineers to collect and analyze data, and to integrate the machine learning models into existing systems and processes. In order to be a successful machine learning engineer, it is essential to have a strong understanding of mathematics, statistics, and programming languages such as Python and R. Additionally, experience with deep learning frameworks such as TensorFlow and PyTorch is highly valued in the industry.

Salary range

EUR 10000 to EUR 15000+ Per Month

Qualifications, training and skills required
  • To be a successful machine learning engineer, one must have a solid background in mathematics, statistics, and computer science. A strong understanding of programming languages such as Python, R, and SQL is essential, as well as experience in using popular machine learning libraries and frameworks. Advanced degree in computer science, statistics or a related field is preferred. In addition to these technical skills, machine learning engineers should possess excellent problem-solving abilities, attention to detail, and a deep understanding of the ethics and safety implications of AI technology. They must also be able to work well in a team, communicate effectively, and be open to continuous learning and growth.
Extra desired training
  • A degree in Computer Science, Mathematics, Statistics, or a related field
  • Strong knowledge of programming languages such as Python, R, or C++
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn
  • Knowledge of data structures, algorithms, and software design principles
  • Understanding of statistical modeling and data analysis
  • Strong understanding of linear algebra, calculus, and probability
  • Experience with big data platforms like Hadoop, Spark, or Apache Flink
  • Excellent problem-solving skills and ability to think outside the box
  • Ability to communicate complex technical concepts to both technical and non-technical stakeholders
  • Good teamwork skills and the ability to collaborate with others effectively.