Key skills
Azure DatabricksMLFlowUnity CatalogDevOps for ML/AICI/CDPipeline automationData architectureSchema evolutionData governanceMicrosoft AzureInfrastructure as CodeTerraformPythonAIMachine LearningMLGenerative AIPyTorchTensorFlowscikit-learnMLflowAnalyticsDatabricksAzureKubernetesDocker
About this role
Ascent, recently acquired by Acuity Analytics, is seeking a Senior DevOps Engineer with expertise in Azure Databricks and cloud-native AI/ML operations. The role involves designing and optimizing ML/AI pipelines, building CI/CD workflows, and ensuring compliance and scalability of AI models in a cloud-native environment.
Responsibilities:
- 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
- Solid knowledge of containerization (Docker) and orchestration (Kubernetes)
- Experience in Python software development and scripting
- Hands-on experience with TensorFlow, PyTorch, and Scikit-learn in a Databricks environment