Aktualne oferty pracy związane z Cloud MLOps Specialist - Wrocław, Województwo dolnośląskie - Xebia
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Senior MLOps Engineer
3 tygodni temu
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Senior MLOps Engineer
5 dni temu
Wrocław, Województwo dolnośląskie, Polska Xebia sp. z o.o. Pełny etatWe are Xebia – a place where experts grow. For nearly two decades now, we've been developing digital solutions for clients from many industries and places across the globe. Among the brands we've worked with are UPS, McLaren, Aviva, Deloitte, and many, many more.We're passionate about Cloud-based solutions. So much so, that we have a partnership with three...
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Data Engineering and MLOps Specialist
3 dni temu
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3 dni temu
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Data Science Infrastructure Specialist
6 dni temu
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MLOps pharma
5 dni temu
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Cloud AI Infrastructure Specialist
1 tydzień temu
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Cloud ML Solutions Architect
2 dni temu
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Artificial Intelligence Infrastructure Specialist
2 tygodni temu
Wrocław, Województwo dolnośląskie, Polska Experis ManpowerGroup Sp. z o.o. Pełny etatDescription: Our team is looking for an artificial intelligence infrastructure specialist to help us build and maintain scalable and efficient AI solutions. As a key member of our hybrid team, you will design and implement architectural setups using LLMs with RAG, APIs, Widgets, and more.Key Tasks:Designing and implementing cloud-based AI solutionsDeveloping...
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Cloud Technology Specialist
3 dni temu
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Cloud MLOps Specialist
3 tygodni temu
Xebia Group is a family of interlinked companies driven by the desire to make a difference in the world of technology. Our mission can be captured in one word: Authority. We want to be recognized as the authority in our field of expertise.
About the role:
Job Description:The MLOps Engineer will play a crucial role in streamlining machine learning project lifecycles by designing and automating workflows, implementing CI/CD pipelines, ensuring reproducibility, and providing reliable experiment tracking. They will work closely with stakeholders and platform engineers to set up infrastructure, automate model deployment, monitor models, and scale training.
Responsibilities:- Collaborate with stakeholders to understand key challenges and inefficiencies in machine learning project lifecycles.
- Design and automate workflows, implement CI/CD pipelines, ensure reproducibility, and provide reliable experiment tracking.
- Work with platform engineers to set up infrastructure, automate model deployment, monitor models, and scale training.