Data Science & AI Expert with Python & Kubernetes / Argo Workflows (f/m/d) ID 25970-0

This is a remote position.

Data Science & AI Expert with Python & Kubernetes / Argo Workflows (f/m/d) ID 25970-0

Offsite Stunden:                              900

Gewünschtes Eintrittsdatum:            13.01.2025

End-Datum:                                    30.06.2025

Project Description

In an effort to improve development speed, quality and maintainability, we are building a set of reusable components to be used in the context of Data Science & AI.

The ultimate goal is to enable data scientists to work without the need for ML engineers, while following best engineering and security practices.

We follow the GitOps principle, so most of our components consist of templates that set up infrastructure and pipelines through CI/CD.

We also maintain reusable Docker images and Python libraries that are often used in the templates.

Some examples of components

- Automated data ingestion, including versioning, validation against expectations, data drift checking

- ML lifecycle: from experiments to predictions via pipelines running on Kubernetes (Argo workflows) and DVC

- Documenting in markdown and publishing beautiful web pages using mkdocs

- Set up Python packages, including CI/CD with pre-commit checks, testing, integration with SonarQube, build and deployment

We constantly push the boundaries of what we do to stay current with best practices, and in some cases, lead the way.

We prefer open source solutions whenever possible.

Technical Skills

TDD and DevOps practices are second nature to you.

Tools:

• GitLab CI/CD

• Python

• Kubernetes

• Argo Workflows

• Argo CD

• jinja2 and copier

• terraform

Tasks Description

• You will consult a team of 7 ML Engineers, primarily working within a sub-team of 3 dedicated to developing and maintaining reusable components. (The remaining team focuses on maintaining the underlying infrastructure, like Kubernetes and Argo Workflows.)

• Actively contribute to the Agile team’s setup, and be open minded about processes you are new to

• Develop new components as outlined in the project description, including automated data ingestion, ML lifecycle management, and documentation tools. Enhance existing components by adding new features and improvements.

• Provide support to users (primarily data scientists and other ML engineers) by troubleshooting issues, answering queries, and ensuring effective use of the developed components.

• Independently drive the development and continuous improvement of components, proactively identifying areas for enhancement.

• Contribute to and maintain comprehensive user and developer documentation to ensure ease of use and adoption of the components.

• Participate in peer reviews of code and documentation to uphold high-quality standards and knowledge sharing within the team.

• Design and implement comprehensive test suites to ensure the reliability, robustness, and high quality of all components, maintaining consistent standards across the development lifecycle.

Soft Skills

You enjoy precision work and attention to detail.

You feel rewarded when you are able to reduce complexity, and you constantly strive for the simplest design possible.

Ability to communicate complex concepts in simple, accessible, and entertaining language.