Senior MLOps Engineer: Scalable ML Deployments & CI/CD

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

Benefits offered by this job

Medical plan

Dental plan

Vision plan

401(k) plan

Employee stock purchase plan

Job summary

TriNet is seeking a Staff MLOps Engineer to design, implement, and optimize machine learning operations within our infrastructure. You will collaborate with data scientists, software engineers, and DevOps to deploy and maintain ML models.

Responsibilities include building scalable infrastructure for model deployment, automating training pipelines with CI/CD, monitoring models in production, and ensuring data privacy and governance. Strong engineering and cloud experience required.

Qualifications

• Bachelor's degree in Computer Science/Engineering or equivalent experience.
• 8+ years proven experience in MLOps or DevOps in a technical engineering environment.
• Proficiency with Python/Java and ML frameworks (TensorFlow, PyTorch).

Responsibilities

• Develop, manage, and scale ML deployment infrastructure with orchestration, version control, and monitoring.
• Design automation pipelines for model training, testing, validation, and deployment using CI/CD practices.
• Deploy ML models to production and establish monitoring, alerting, and data drift tracking.
• Collaborate with data scientists, software engineers, and DevOps to integrate ML solutions into systems.
• Ensure security compliance and data privacy throughout the ML lifecycle.

Skills

Python

Docker

Kubernetes

CI/CD

Education

Bachelor's Degree in Computer Science/Engineering or equivalent experience

Tools

Git

Tableau

TensorFlow

Job description

TriNet is seeking a Staff MLOps Engineer to design, implement, and optimize machine learning operations within our infrastructure. You will collaborate with data scientists, software engineers, and DevOps to deploy and maintain ML models.

Responsibilities include building scalable infrastructure for model deployment, automating training pipelines with CI/CD, monitoring models in production, and ensuring data privacy and governance. Strong engineering and cloud experience required.