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Machine Learning Engineer



  • Develop machine learning end-to-end applications or modules into production environments according to the requirements.
  • Implementing machine learning deployment pipelines (ML Ops).
  • Integrate designed machine learning models in currently developed applications.
  • Define the architecture of machine learning systems.
  • Select appropriate data sets and data representation methods.
  • Perform statistical analysis and fine-tuning using test results.
  • Train and retrain ML systems when necessary.
  • Apply software engineering best practices.
  • Run machine learning tests and experiments.


Qualifications and Experience

  • Knowledge and understanding of AI and Machine Learning.
  • Strong experience building MLOps pipelines; experience in Dataiku is a plus.
  • Knowledge of frameworks such as Keras, PyTorch, Tensorflow, Spark ML
  • Familiar with cloud ML tools like Google Cloud ML Engine, Amazon Machine Learning


About Endava

Endava is reimagining the relationships between people and technology. For the past 20 years it has helped some of the world's leading Finance, Insurance, Telecommunications, Media, Technology and Retail companies accelerate their ability to take advantage of new business models and market opportunities. We have more than 8200 employees located in close to client locations in Denmark, Germany, Netherlands, United Kingdom, United States and nearshore delivery centers in the EU: Romania, Bulgaria, Croatia and Slovenia; Central European Countries: North Macedonia, Moldova, Serbia and Bosnia and Herzegovina; Latin America: Argentina, Colombia and Uruguay.

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