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Machine learning ops engineer

Meyrin
Inserat online seit: Veröffentlicht vor 8 Std.
Beschreibung

How will you make an impact?HOW WILL YOU MAKE AN IMPACT?
1. Develop components of the analytics and machine learning platform, including: infrastructure modules, reusable components for AI/Analytics applications or architecture templates
2. Industrialize, maintain and improve AI and analytics solutions in Google Cloud Platform
3. Manage the infrastructure with special focus on reliance, security and scalability
4. Partner with Analytics Engineers, Data Scientists, Infrastructure & Data Engineers for the project delivery

HOW WILL YOU EXPERIENCE SUCESS WITH US?

5. Graduate in Master program in Engineering, Data Science, or related fields or equivalent professional experience
6. Proficient in Python programming & SQL (5 years or more)
7. Practical experience in MLOPs (3-5 years or more)
8. Professional experience in Google Cloud Platform (2 years +)
9. Practical experience with infrastructure as a code, ideally Terraform (1 years +)
10. Knowledge of Data Engineering principles
11. Knowledge of REST API and microservices
12. A dynamic, innovative & pragmatic mindset to problem solving, and an ability to think critically and objectively, both independently & within a team
13. Proactive, curious and autonomous with a strong sense of ownership and always on the look to improve the current solutions
14. Strong communication skills, English is a must, ease to collaborate in multicultural and multifunctional environments
15. Experience in Vertex AI and DBT is a plus

WHAT MAKES OUR GROUP DIFFERENT?

This is a fantastic opportunity to join the leader of luxury digital distribution as a builder of excellence for such a transformational practice. The business impact up for grasps, the AI use cases and diversity of stakeholders will make it rich, fast-paced, multicultural and fun for the right candidate.

YOUR JOURNEY WITH US:

1. If your application is selected, we will reach out to you ASAP for an informal introductory call.

2. The next step from there would be interviews with the Head of Data platform, Data Engineering team lead and our HR Business Partner.

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