Senior MLOps Engineer - Scale ML Deployments & CI/CD

Trinet; Clarkston (GA); On-site; USD 125,000 - 275,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Stock purchase plan

11 company holidays

Paid time off

Job summary

TriNet is seeking a Staff MLOps Engineer to design, implement, and optimize ML operations within our infrastructure. You will collaborate with data scientists, software engineers, and DevOps to ensure reliable deployment and maintenance of ML models.

You will shape automated pipelines for model training, testing, and deployment, using CI/CD practices and containerized deployments in AWS/GCP/Azure environments. Strong communication and problem-solving skills are essential.

Qualifications

• Bachelor's Degree in Computer Science/Engineering or equivalent experience preferred.
• 8+ years of experience in MLOps/DevOps in a technical engineering environment.
• Experience with Python/Java and ML frameworks like TensorFlow or PyTorch.
• Experience with CI/CD pipelines, Git, and automation tools.

Responsibilities

• Develop, manage, and scale infrastructure for ML model deployment and monitoring.
• Design automated pipelines for training, testing, validation, and deployment with CI/CD.
• Deploy ML models to production with monitoring, health checks, and data drift alerts.
• Collaborate with data scientists, software engineers, and DevOps teams.
• Ensure security and governance across ML lifecycle and data privacy.

Skills

MLOps concepts

Data pipelines

Python/Java

CI/CD

Docker/Kubernetes

AWS/Azure/GCP

Tableau

SDLC

Communication

Problem solving

Education

Bachelors in CS/Engineering

Tools

Git

CI/CD pipelines

Tableau

Job description

TriNet is seeking a Staff MLOps Engineer to design, implement, and optimize ML operations within our infrastructure. You will collaborate with data scientists, software engineers, and DevOps to ensure reliable deployment and maintenance of ML models.

You will shape automated pipelines for model training, testing, and deployment, using CI/CD practices and containerized deployments in AWS/GCP/Azure environments. Strong communication and problem-solving skills are essential.