Machine Learning Engineer

• From Ideas to Action: Translate ideas into prototypes and then into production using MLOps best practices. This role extends beyond just modeling in Jupyter notebooks. You will also be responsible for deploying data science solutions, maintaining them, and further developing our solutions.
• Unleash Your Innovative Spirit: Dive into new technologies in your daily tasks, dedicated hacking days, or sprints. We encourage a culture of active exploration, seeking and applying the latest advancements to improve existing products and create new ones.
• Own Your Impact: Take full ownership of features and products from inception to deployment. Your contributions will directly shape the success and evolution of our solutions.
• Team-Driven Development: Influence our products and foster a collaborative culture through code reviews, pair programming, and knowledge sharing.
• Stay Ahead of the Curve: Continuously update your skills and knowledge with the latest industry trends and technologies.

• Ability to translate ideas into prototypes and then into production, taking ownership of all steps in the product lifecycle.
• Experience deploying models on cloud platforms such as GCP or AWS
• Experience with cloud services such as BigQuery, Vertex AI, Workflows, Dataflow, etc.
• Experience with DevOps technologies such as Docker, Kubernetes, and CI/CD
• Experience with cloud infrastructure-as-code (IaC) tools like Terraform or AWS CloudFormation
• Agile mindset with motivation for continuous self and team development in a collaborative work environment.

• German A2 (basic knowledge) and English C1 (proficient user) Language level Nice-to-have:

• Familiarity with LLMs, RAG, and image generation using both commercial and open-source models
• Knowledge of additional programming languages, such as Java/ Go/Rust for backend development or JavaScript for frontend development

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