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Machine Learning Engineer (Budapest, remote)

We are looking for a Machine Learning Engineer who will support our clients as they begin their journey on the Google Cloud Platform (GCP).

This role will suit you if

  • you want to work with A+ colleagues, who are also the region’s most experienced GCP developers.
  • you have ambitions both to solve customer requirements in a dynamic project environment and contribute to the development of our ML products.
  • working with different people on different problems is refreshing for you.
  • keeping your knowledge up-to-date is just as important to you as sharing it.
You will be responsible for

  • deploying and scaling end-to-end ML solutions, solving operational problems.
  • transforming ML experiments into production-ready, stable solutions.
  • implementing your ideas and creating structured code.
  • using your expertise to automate and optimize workflows.
  • holding technical training sessions and workshops for our customers.
You will need

  • a university degree in a technical field or equivalent data science or ML engineering experience.
  • 5+ years of relevant experience (minimum 2 years in data and/or the ML field).
  • proficiency in writing software with Python in a collaborative environment.
  • a thorough understanding of data science workflows, especially in production-level model deployment, operation, and artifact management aspects.
  • solid knowledge of data processing with SQL and with Python libraries (e.g. pandas, Dask, PySpark)
  • a deep understanding of software development lifecycles and engineering practices (data pipelines, API workflows, CI/CD, containerization, observability, and security) – knowledge of ML Ops principles, techniques, and tooling is a plus.
  • curiosity and a passion to learn new methodologies and technologies.
  • good communication skills in English.
It would be nice if you also had

  • a minimum of 2 years’ experience in data engineering (using Google BigQuery, Apache Beam, Apache Airflow, etc.)
  • familiarity with ML libraries, such as scikit-learn, Tensorflow, or Pytorch.
  • client-facing skills and consulting experience.
  • hands-on experience with cloud computing.
  • knowledge of ML Ops principles, techniques, and tooling
  • experience in building ML pipelines with Kubeflow, Apache Airflow, Apache Beam, Vertex AI, TFX or with Sagemaker Pipelines.
  • good communication skills in German.
You will have the opportunity to

  • use cutting-edge technologies.
  • learn from A+ big data and Google Cloud experts and mentor talented juniors.
  • learn as part of your job by capitalizing on our company-level knowledge management system.
  • maintain a healthy work-life balance by taking advantage of our flexible working hours and home office support.
  • travel to cool places, such as Singapore (when COVID allows).

Ready to apply?

Questions?

Drop us an email at recruitment@aliz.ai.

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