The company is seeking a Machine Learning Engineer to build, deploy, and maintain machine learning models and their associated data pipelines within Azure environments to deliver insights, automation, and models for their customers.
Requirements
- Proficiency in Python, SQL, and Azure services (Azure ML, Synapse, Data Factory, Data Lake).
- Experience deploying ML models into production environments.
- Strong understanding of statistics, data modeling, and MLOps best practices.
- Experience with Azure DevOps, GitHub Actions, or similar CI/CD tools.
- Knowledge of data governance, SOC 2 compliance, and ML model monitoring.
- Familiarity with Power BI or similar visualization tools.
Responsibilities
- Design, develop, train, deploy, and support machine learning models using Python, SQL, Azure Machine Learning, AutoML.
- Build, test, and monitor predictive models for performance and accuracy.
- Automate model training, scoring, and deployment workflows using Azure DevOps and ML pipelines.
- Develop and maintain ETL/ELT pipelines using Azure Data Factory, Synapse, and Python.
- Manage and optimize relational and cloud-based data stores for analytics and ML workloads.
- Leverage Azure services (Functions, Logic Apps, Event Hubs) for event-driven and automated data processing.
- Utilize CI/CD pipelines for automated model deployment, versioning, and rollback.
Other
- FULL TIME POSITION.
- 5-7 years of experience in data engineering, machine learning, or related roles.
- Excellent problem-solving and communication skills.
- Work cross-functionally with product, engineering, and risk teams to deliver data-driven solutions.
- Translate analytical and technical results into actionable insights for business stakeholders.
