Data Engineer (Machine Learning)

This is a remote position.

A Data Engineer (Machine Learning) is required to lead platform engineering, deployment automation, and artificial intelligence and machine learning model deployment within a cloud environment. The role focuses on delivering secure, scalable, and cost efficient solutions while supporting full lifecycle management of machine learning models and advanced data engineering initiatives. Responsibilities include designing and implementing continuous integration and continuous deployment pipelines, managing multi environment deployments, automating infrastructure provisioning, and ensuring reliable platform performance across development, testing, and production environments.

The position involves deploying and managing artificial intelligence and machine learning models for both batch and real time inference, implementing lifecycle management practices, and developing scalable application programming interface based solutions for model serving and system integration. Additional responsibilities include building and optimizing data pipelines and data models, ensuring data quality and governance, implementing secure cloud architectures, managing access controls and secrets, and optimizing cloud resource usage. The role also supports integration with internal and external systems, monitors system performance and model drift, and contributes to incident response, cost governance, and continuous improvement of architecture and processes.

Qualifications

• 10+ years - Information technology experience with strong focus on DevOps, MLOps, or Data Engineering
• 10+ years - Designing and implementing continuous integration and continuous deployment pipelines using Azure DevOps, Git, and YAML
• 10+ years - Deploying artificial intelligence and machine learning models into production using automated pipelines
• 10+ years - Implementing model lifecycle management including training, validation, deployment, and monitoring
• 10+ years - Designing and building data pipelines using Azure Data Factory, Databricks, and Azure Data Lake Storage
• 5+ years - Infrastructure as Code using ARM, Bicep, or Terraform
• 5+ years - SQL and relational databases including Azure SQL and Oracle
• 5+ years - REST API development and integration
• 5+ years - Cluster management, scaling, and performance optimization

Nice to Have

• Experience with Azure AI Search and Azure AI Foundry
• Experience with event driven architecture including Event Grid or Service Bus
• Experience with streaming platforms such as Kafka or Event Hubs
• Experience with containerization technologies including Docker, Kubernetes, or Azure Kubernetes Service
• Experience with large language models or generative artificial intelligence pipelines
• Familiarity with data governance practices and medallion architecture
• Strong problem solving and troubleshooting abilities
• Ability to collaborate across DevOps, data, and machine learning teams
• Strong communication and documentation skills
• Leadership and mentoring capabilities