Data Scientist & ML Engineer, On-Prem Production Pipelines

Rhox

Brussel

Sur place

EUR 70 000 - 110 000

Plein temps

Il y a 7 jours
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Résumé du poste

Rhox is seeking a mid-level Data Scientist and ML Engineer to design end-to-end ML systems and deploy AI models in production, primarily on-premise with Azure, Docker and Kubernetes.

The role involves handling large datasets across SQL and NoSQL, building reusable pipelines, versioning code and models, and collaborating with operational stakeholders to translate investigative needs into reliable AI capabilities.

Qualifications

  • Minimum 3 years of professional experience in data science, ML and MLOps, including production or large-scale deployments.
  • Design and operate on-premise and cloud AI solutions, with hands-on experience in Azure.
  • Program confidently in Python and apply PyTorch, TensorFlow and huggingface to machine learning or deep learning work.
  • Use Docker, Kubernetes and Kubeflow to containerise and orchestrate ML workloads.
  • Work with MySQL, PostgreSQL, Neo4J and Milvus across relational, graph and vector data use cases.
  • Implement MLOps and CI/CD workflows with MLflow, Git, GitHub and GitLab, and enforce code quality with ruff.
  • Handle large structured and unstructured datasets and communicate technical concepts clearly to non-technical stakeholders.
  • Approach problems analytically, collaborate across different profiles and apply careful attention to quality, security and legal compliance.

Responsabilités

  • Design end-to-end machine learning systems that meet scalability, robustness, maintenance and hardware constraints.
  • Develop, train and validate models for operational and tactical use, working with large structured and unstructured datasets.
  • Build and operate on-premise machine learning pipelines, then move validated models into production with monitoring and maintenance.
  • Containerise and orchestrate workloads with Docker, Kubernetes and Kubeflow.
  • Establish CI/CD workflows for ML code and models, including versioning, testing and reproducible releases.
  • Apply clear documentation, code quality standards and appropriate security, ethical and legal controls.

Connaissances

Data science
Machine learning
MLOps
Python
Docker
Kubernetes
Kubeflow
PyTorch
TensorFlow
HuggingFace

Formation

Master’s degree or doctorate in computer science or related field

Outils

Azure
Docker
Kubernetes
Kubeflow
MLflow
Git
GitHub
GitLab
MySQL
PostgreSQL
Neo4J
Milvus
PyTorch
TensorFlow
HuggingFace

Description du poste

Rhox is seeking a mid-level Data Scientist and ML Engineer to design end-to-end ML systems and deploy AI models in production, primarily on-premise with Azure, Docker and Kubernetes.

The role involves handling large datasets across SQL and NoSQL, building reusable pipelines, versioning code and models, and collaborating with operational stakeholders to translate investigative needs into reliable AI capabilities.

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