Requirements

Expected technologies

MLOps

Python

SQL

CI/CD

Operating system

Windows

macOS

Linux

Our requirements

• 2+ years of experience developing and deploying machine learning systems into production,
• 5+ years of experience as a MLOps engineer or data engineer or software developer,
• hands-on experience with cloud environments (AWS / Azure / GCP),
• experience with tools such as Spark, PyTorch, TensorFlow and MLFlow,
• knowledge of DevOps practices and tools, including Terraform,
• experience with Docker and Kubernetes,
• understanding of continuous integration and continuous deployment (CI/CD) practices, as well as experience with related tools like GitHub Actions or GitLab CI,
• excellent verbal and written communication skills in English.
• Work from the European Union region and a work permit are required.
• Candidates must have an active VAT status in the EU VIES registry: https://ec.europa.eu/taxation\_customs/vies.

Optional

• Cloud (Azure, AWS, GCP) certification is a big plus,
• familiarity with Amazon SageMaker / Azure Machine Learning/ Azure Machine Learning / VertexAI is nice to have.

Your responsibilities

• collaborating with Platform Engineers to set the infrastructure required to run MLOps processes efficiently,
• implementing ML workflows / automating CI/CD pipelines,
• automating model deployment and implementing model monitoring,
• collaborating with Platform Engineers to implement backup and disaster recovery processes for ML workflows, especially models and experiments,
• collaborating with stakeholders to understand the key challenges and inefficiencies of Machine Learning project lifecycles within the company,
• keeping on top of the latest trends and advancements in data engineering and machine learning.