MLOps Engineer: Deploy, Scale & Automate ML Pipelines

NEXTGEN Healthcare; Atlanta (GA); On-site; USD 110,000 - 170,000; Full time

Job summary

NextGen Healthcare is seeking an MLOps Engineer to streamline deployment, monitoring, and scaling of ML models in production environments. You will collaborate with data scientists, software engineers, and product teams to deliver reliable operational solutions.

Responsibilities include designing scalable infrastructure for training, testing, and serving models, automating data preprocessing and deployment workflows, and monitoring model performance and resource usage to optimize latency and

Qualifications

• Bachelor's degree in CS/DS/Engineering or related field.
• 2-3 years of hands-on MLOps/DevOps experience.
• Experience with MLOps tools: MLflow, Kubeflow, SageMaker.
• Experience with feature stores and model versioning.
• Experience building CI/CD pipelines: Jenkins, GitLab CI.

Responsibilities

• Implement and maintain CI/CD pipelines for deploying ML models to production environments.
• Ensure seamless integration of ML models into existing software systems.
• Design and manage scalable infrastructure for training, testing, and serving ML models.
• Automate data preprocessing, model training, and deployment workflows.
• Monitor performance, latency, scalability, and resource usage.
• Collaborate with data scientists, software engineers, and product teams.
• Maintain version control for datasets, models, and code.
• Stay updated with the latest trends in MLOps tools, frameworks, and practices.
• Perform other duties supporting the overall objective of the position.

Skills

Problem-solving

Attention to detail

Communication

Collaboration

Education

Bachelor's degree in Computer Science, Data Science, Engineering, or related field

Tools

MLflow

Kubeflow

SageMaker

Jenkins

GitLab CI

Docker

Kubernetes

Apache Spark

SQL

NoSQL

Job description

NextGen Healthcare is seeking an MLOps Engineer to streamline deployment, monitoring, and scaling of ML models in production environments. You will collaborate with data scientists, software engineers, and product teams to deliver reliable operational solutions.

Responsibilities include designing scalable infrastructure for training, testing, and serving models, automating data preprocessing and deployment workflows, and monitoring model performance and resource usage to optimize latency and