ZAUBAR
Ml Ops Engineer (Remote)
Ml Ops Engineer | ZAUBAR | Germany
Ml Ops Engineer | ZAUBAR | Germany
We’re looking for an experienced Machine Learning Engineer to join our expanding team. Your role will encompass designing and implementing Deep Learning Pipelines using cutting-edge models, maintaining our Azure infrastructure, and establishing automated deployment pipelines. Staying abreast with AI trends and refining pipeline prototypes alongside the team and clients until perfected will also be key.
In a fast-paced environment where your code is quickly deployed, you’ll have a high degree of ownership over product code and work closely with the team and creative and product teams to prioritize issues and opportunities. At ZAUBAR, we provide everything needed to succeed in a dynamic, employee-centric structure where you are entrusted with making time travel possible. If you’re a motivated individual with a passion for machine learning, we’d love to hear from you.
Tasks
We make use of the following stack:
- Cloud platform: Azure
- Deep learning framework: Pytorch
- CI/CD tools: Pytest, Github Actions, Docker
- Infrastructure as code tool: Terraform
Job Functions:
- Develop and implement Deep Learning Pipelines using cutting-edge models
- Sustain the infrastructure for Deep Learning inference on Azure
- Build a CI/CD pipeline for automated deployment
- Keep up-to-date with latest developments in the AI field
- Prototype the pipelines and refine them with the team and clients until the final product
Additional tasks will include:
- Managing the AI inference backend, facilitating secure frontend requests
- Designing and implementing database schema and serverless architectures
Requirements
- At least 3 years of experience with Deep Learning Pipelines
- Knowledge and experience with Azure/AWS/GCP, preferably Azure
- An approachable and friendly disposition
- The ability to see through problems to their resolution
Benefits
We provide an attractive salary and benefits package, including flexible working hours, the option to work remotely, and avenues for career advancement. If you are a highly driven individual with a fervor for machine learning, we encourage you to reach out to us!
- Please attach a portfolio of your work.
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