Job Title: MLOps Engineer (Forecasting) Location: Remote (USA) Industry: Healthcare About the Role
We are seeking an experienced MLOps Engineer with strong expertise in forecasting models, Azure Cloud, and Databricks to support a healthcare-focused analytics initiative. This role will be responsible for building, deploying, automating, and maintaining machine learning solutions while ensuring reliability, scalability, and operational excellence throughout the ML lifecycle.
The ideal candidate will have hands-on experience with forecasting and time-series models, cloud-based ML deployments, MLOps best practices, and production support of machine learning systems. Key Responsibilities
Design, develop, test, and deploy machine learning forecasting models.
Build and maintain scalable data pipelines in collaboration with data engineering teams.
Perform feature engineering and feature selection to improve model performance and accuracy.
Monitor, evaluate, and optimize forecasting models using appropriate performance metrics.
Implement MLOps best practices including CI/CD pipelines, model versioning, automation, and deployment frameworks.
Manage production deployments, model monitoring, retraining processes, and operational support.
Troubleshoot model performance issues and support ongoing maintenance activities.
Document machine learning models, workflows, deployment processes, and operational procedures.
Collaborate with cross-functional teams including Data Engineers, Data Scientists, and business stakeholders.
Required Qualifications
3+ years of experience in MLOps, Machine Learning Engineering, or Data Science.
Strong programming experience with Python and R.
Hands-on experience with Azure Cloud services.
Experience using Databricks for data processing, model development, and machine learning workflows.
Strong understanding of forecasting techniques and time-series modeling.
Experience building and managing CI/CD pipelines for machine learning deployments.
Experience with model deployment, monitoring, automation, and production support.
Familiarity with machine learning frameworks such as Scikit-Learn and TensorFlow.
Preferred Qualifications
Experience with MLflow, Azure Machine Learning, or similar MLOps platforms.
Azure certifications.
Experience deploying machine learning models in cloud environments.
Exposure to advanced forecasting and predictive analytics techniques.
Healthcare domain experience is a plus.
Numbers & Facts
Location
Princeton, NJ (Remote)
Skills
Automationunmatched
Best Practicesunmatched
Cloud Computingunmatched
Computer Programmingunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Cross-Functionalunmatched
Data Managementunmatched
Data Modelingunmatched
Data Processingunmatched
Data Scienceunmatched
Documentation Modelsunmatched
Equipment Maintenance/Repairunmatched
Forecastingunmatched
Healthcareunmatched
Identify Issuesunmatched
Machine Learningunmatched
Microsoft Windows Azureunmatched
Operational Supportunmatched
Operations Processesunmatched
Performance Managementunmatched
Performance Metricsunmatched
Performance Modelingunmatched
Predictive Modelingunmatched
Production Managementunmatched
Production Supportunmatched
Python Programming/Scripting Languageunmatched
R Programming Languageunmatched
Scalable System Developmentunmatched
Test Plan/Scheduleunmatched
🎯
Be found by employers
5,500+ employers search our resume database daily. Add yours to get found by recruiters looking for candidates like you.
Level up your application
Professional resume templates
Browse dozens of recruiter approved resume templates, layouts and formats. Choose your favorite and make it your own in minutes.