MLOps Engineer – Scalable ML Deployments & CI/CD

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

Benefits offered by this job

Medical benefits

Dental & Vision

401(k) plan

Paid time off

Job summary

TriNet in Atlanta, GA is seeking a Staff MLOps Engineer to design, implement, and optimize ML operations across our infrastructure. You will collaborate with data scientists, software engineers, and DevOps to deploy models, automate training pipelines with CI/CD, and monitor model health and data drift.

The role requires 8+ years in MLOps/DevOps, strong Python/Java, and experience with Docker, Kubernetes, and cloud platforms; telework options may be available.

Qualifications

• Bachelor's Degree in Computer Science/Engineering or equivalent experience preferred.
• Typically 8+ years in an MLOps or DevOps role within a technical engineering environment.
• Experience with Python, Java, and ML frameworks (TensorFlow, PyTorch).
• Experience with CI/CD pipelines, version control systems, and automation tools.

Responsibilities

• Develop, manage, and scale ML model deployment infrastructure.
• Design and implement automation pipelines for model training, testing, validation, and deployment with CI/CD.
• Deploy ML models to production with monitoring for performance, health, and data drift.
• Collaborate with data scientists, software engineers, and DevOps to integrate ML solutions into systems.

Skills

Python

Java

TensorFlow

PyTorch

CI/CD

Git

Docker

Kubernetes

AWS

Azure

GCP

Tableau

EDW

Data Lake

Data warehouse

Dimensional Modeling

Education

Bachelor's Degree in Computer Science/Engineering

Tools

Docker

Kubernetes

Git

Job description

TriNet in Atlanta, GA is seeking a Staff MLOps Engineer to design, implement, and optimize ML operations across our infrastructure. You will collaborate with data scientists, software engineers, and DevOps to deploy models, automate training pipelines with CI/CD, and monitor model health and data drift.

The role requires 8+ years in MLOps/DevOps, strong Python/Java, and experience with Docker, Kubernetes, and cloud platforms; telework options may be available.