We're looking for a to build and deploy solutions, including production AI on-premise and in the cloud. You'll develop pipelines and take models through deployment, monitoring and maintenance.
What you'll do:
- Build and deploy pipelines and AI models, mainly on-premise.
- Monitor and maintain deployed models and pipelines.
- Apply programming and standards across projects.
- Work with large structured and unstructured datasets.
- Track developments in machine learning and .
What you bring:
- A or in computer science, AI or an equivalent field.
- At least three years' industry experience in , machine learning and , including large-scale deployments.
- Strong theoretical and practical knowledge of machine learning and .
- Experience developing and deploying AI on-premise and in the cloud, including .
- Experience with , , Kubeflow and MLflow pipelines.
- , ruff, Git, and .
- , PyTorch and TensorFlow.
- Experience with relational and databases, including , , and Milvus.
- Experience implementing for ML models and supporting code.
- Experience with data lakes, data warehouses and object storage.
- Experience designing end-to-end ML systems for scalability, robustness, maintenance and hardware constraints.
- Clear communication, analytical problem-solving and constructive collaboration, including explaining technical concepts to non-technical colleagues.
- (B2) and or (B2).
What's next?
The people who do well here are the ones who saw themselves in this description. Not because they match every line, but because the mission felt right for them.
We are actively hiring for this position. Applications are reviewed by our team, and matching profiles receive a call to discuss the role in detail.
It takes under a minute to apply. Your email, your CV. That is all we need to start the conversation.