What You Will Do
- Develop ML Models: Assist in the design and implementation of machine learning models to solve specific business problems.
- Implement MLOps: Build and maintain CI/CD pipelines using Azure DevOps to automate the testing and deployment of ML models.
- Manage Infrastructure: Use Terraform to provision and manage cloud infrastructure across Azure and Google Cloud Platform (GCP).
- Monitor & Optimize: Track model performance in production and optimize infrastructure for cost and efficiency.
- Collaborate on Architecture: Work with the engineering team to ensure data science code is production-ready and integrates smoothly with existing systems.
What You Bring
- Experience: 3+ years of experience (or relevant internships/projects) in Data Science, DevOps, or Software Engineering.
- Technical Expertise: Proficiency in Python and SQL. Knowledge of API development with FastAPI.
- DevOps Knowledge: Hands-on experience or strong familiarity with Azure DevOps, CI/CD concepts, Docker and version control (Git).
- Cloud Experience: Familiarity with cloud services in Microsoft Azure and Google Cloud Platform (GCP). Practical knowledge of Terraform for managing cloud resources.
- Education: A relevant degree in Computer Science, Data Science, or Engineering is required.
If you have any questions,
check out our or call Yuliya Stoyko at +34 917095993. For this vacancy we only accept direct applications in English. Diversity is important to us. Therefore, we are looking to receiving applications regardless of any personal background.
What We Offer
Flexible Work Models
We trust our employees and offer a work environment that is well-balanced, productive and fosters success.
Personal Development
You will benefit from a culture of continuous learning and feedback. Your personal growth is supported through an extensive learning offering.
Agile Working Methods
Whether through scrum or design thinking,
we solve exciting tasks together in teams.