Remote Senior MLOps Engineer — Azure & Databricks

North Eastern Services; United States; Remote; USD 140,000 - 220,000; Full time

Job summary

Fusemachines is hiring a Senior MLOps Engineer to design, automate, deploy, monitor, and govern ML systems on Azure. You will partner with data scientists and engineers to operationalize ML solutions, establish standards, and build scalable, reliable ML platforms focused on productionization, deployment, and governance rather than model development.

Role emphasizes automated testing, model monitoring, and security governance via Unity Catalog and Azure security services, with a strong emphasis

Qualifications

• Extensive experience designing end-to-end MLOps workflows
• Ability to productionize data science assets into deployable Python packages
• Proven track record building CI/CD pipelines for ML models and features
• Experience with model lifecycle management and monitoring in cloud environments

Responsibilities

• Design, implement, and maintain end-to-end MLOps workflows for training, deployment, monitoring, retraining, and retirement.
• Productionize notebooks into modular, testable Python packages and services.
• Build and manage CI/CD pipelines for ML models, features, and data products.
• Implement model lifecycle management using MLflow, including registry, versioning, approvals, and rollback.
• Develop feature engineering pipelines using Databricks Feature Engineering and Delta Lake.
• Deploy and operate batch, streaming, and real-time inference on Databricks, Azure ML, and Kubernetes.
• Establish automated testing, validation, and release processes for ML code, data, features, and models.

Skills

Azure Databricks

MLflow

Databricks Feature Engineering

Azure Machine Learning

PySpark

CI/CD

containerization

cloud-native software engineering

Tools

Azure Databricks

MLflow

Kubernetes

Delta Lake

Job description

Fusemachines is hiring a Senior MLOps Engineer to design, automate, deploy, monitor, and govern ML systems on Azure. You will partner with data scientists and engineers to operationalize ML solutions, establish standards, and build scalable, reliable ML platforms focused on productionization, deployment, and governance rather than model development.

Role emphasizes automated testing, model monitoring, and security governance via Unity Catalog and Azure security services, with a strong emphasis