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Machine Learning and MLOps Engineer
You turn data science into running systems: feature pipelines, model deployment and serving, monitoring and retraining, on Fabric, Databricks and Azure Machine Learning, with the cost and reliability of a production service.
Machine Learning and MLOps Engineer
What you will do
- Build feature pipelines, training workflows and model serving
- Implement MLflow or Azure Machine Learning tracking, registries and CI/CD
- Monitor drift, accuracy by horizon and cost; define retraining triggers
- Work with data scientists and engineers to productionize models cleanly
What you bring
- Four or more years in machine learning engineering or data engineering
- Python, Spark and SQL; containers and CI/CD
- Databricks, Fabric or Azure Machine Learning in production
- A reliability mindset: tests, monitoring, runbooks
Nice to have
- Delta Live Tables, Databricks Asset Bundles or Terraform
- Real-time inference or streaming experience
Why MJ Insight
Senior work, from day one.
- A team of senior consultants with Fortune 500 experience in consumer goods, medical technology, healthcare and financial services
- Direct ownership of client outcomes, not a slice of a program
- Current platforms: Microsoft Fabric, Power BI, Databricks, Azure AI, Dynamics 365 and the agent frameworks that follow
- A trilingual North American practice: Canada, the United States and Mexico
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