ML Operations Engineer

NextGen Healthcare; Georgia; On-site; USD 80,000 - 120,000; Full time

Job summary

A healthcare technology firm based in Georgia is seeking a Machine Learning Operations (MLOps) Engineer to support AI/ML initiatives. The role involves streamlining model deployment and monitoring, maintaining CI/CD pipelines, and optimizing model performance. Candidates should have a Bachelor's degree and 2-3 years of experience in MLOps, DevOps, or related fields. Ideal candidates will be proficient in Python, experienced with MLOps tools like MLflow and Kubeflow, and possess excellent problem-solving and collaboration skills.

Qualifications

• 2-3 years of hands-on experience in MLOps, DevOps, or related roles.
• Experience with MLOps tools and platforms like MLflow, Kubeflow, or SageMaker.
• Experience in building CI/CD pipelines using tools like Jenkins, GitLab CI, or similar.

Responsibilities

• Streamlining the deployment, monitoring, and scaling of machine learning models in production environments.
• Implement and maintain CI/CD pipelines for deploying models.
• Monitor the performance of deployed models and optimize for latency.

Skills

Proficiency in Python

Containerization and orchestration

Distributed computing frameworks

Database technologies

Problem-solving skills

Education

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

Tools

MLflow

Kubeflow

SageMaker

Jenkins

GitLab CI

Job description

Job Description

The Machine Learning Operations (MLOps) Engineer will support our AI/ML initiatives by streamlining the deployment, monitoring, and scaling of machine learning models in production environments. The incumbent will have a solid understanding of machine learning workflows, DevOps principles, and cloud technologies, with a focus on optimizing machine learning pipelines and ensuring reliable and efficient operations.

Model Deployment and Integration

• Implement and maintain CI/CD pipelines for deploying machine learning models to production environments.
• Ensure seamless integration of machine learning models into existing software systems.

Infrastructure and Automation

• Design and manage scalable infrastructure for training, testing, and serving machine learning models.
• Automate data preprocessing, model training, and deployment workflows.

Monitoring and Optimization

• Monitor the performance of deployed models and systems, identifying and resolving issues proactively.
• Optimize model inference latency, scalability, and resource utilization.

Collaboration

• Work closely with data scientists, software engineers, and product teams to understand requirements and deliver operational solutions.
• Collaborate with DevOps and cloud engineering teams to ensure infrastructure reliability and security.

Data and Model Management

• Maintain version control for datasets, models, and code.
• Implement best practices for data and model governance, ensuring compliance with organizational and regulatory requirements.

Continuous Improvement

• Stay updated with the latest trends in MLOps tools, frameworks, and practices.
• Recommend and implement improvements to the MLOps processes and infrastructure.

Perform other duties that support the overall objective of the position.

Education Required

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• Or, any combination of education and experience which would provide the required qualifications for the position.

Experience Required

• 2-3 years of hands‑on experience in MLOps, DevOps, or related roles.
• Experience with MLOps tools and platforms like MLflow, Kubeflow, or SageMaker.
• Experience with feature stores and model versioning systems.
• Experience in building CI/CD pipelines using tools like Jenkins, GitLab CI, or similar.

Knowledge, Skills & Abilities

• Proficiency in Python and familiarity with a strong understanding of containerization and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with distributed computing frameworks (e.g., Apache Spark), knowledge of cloud platforms such as AWS, Azure, or Google Cloud, solid understanding of model monitoring, logging, and debugging tools.
• Familiarity with database technologies and data pipelines (SQL, NoSQL, ETL/ELT processes).
• Strong problem‑solving skills and a detail‑oriented mindset; excellent communication and collaboration abilities.

NextGen Healthcare is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.