Key skills
AzureCloudDockerKubernetesPythonPyTorchScikit-LearnTensorflowTerraformUnityAIMachine LearningMLGenerative AITensorFlowscikit-learnMLflowDatabricksCI/CD
About this role
Role Overview
- Design, implement, and optimize ML/AI pipelines for training, deployment, monitoring, and governance.
- Leverage Azure Databricks capabilities including MLFlow for experiment tracking and Unity Catalog for data governance.
- Build and maintain CI/CD pipelines as well as automated ModelOps workflows for AI/ML applications.
- Ensure data architecture supports schema evolution, governance, and compliance requirements.
- Operate in a cloud-native Azure environment to deliver robust and scalable ML solutions.
Requirements
- Proven experience with Azure Databricks, including MLFlow and Unity Catalog.
- Strong background in DevOps for ML/AI, including CI/CD and pipeline automation.
- Solid understanding of data architecture, schema evolution, and governance principles.
- Experience working in Microsoft Azure or similar cloud environments.
- Hands-on experience with Infrastructure as Code (IaC) using Terraform.
- High-level understanding of machine learning and generative AI concepts and workflows (Nice to Have).
- Solid knowledge of containerization (Docker) and orchestration (Kubernetes) (Nice to Have).
- Experience in Python software development and scripting (Nice to Have).
- Hands-on experience with TensorFlow, PyTorch, and Scikit-learn in a Databricks environment (Nice to Have).
Tech Stack
- Azure
- Cloud
- Docker
- Kubernetes
- Python
- PyTorch
- Scikit-Learn
- Tensorflow
- Terraform
- Unity
Benefits
- People are at the Heart of our Business.
- By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.