Senior MLOps Engineer - Scalable ML Deployments & CI/CD

Mosaic.tech; Atlanta (GA); Hybrid; USD 125,000 - 275,000; Full time

Benefits offered by this job

Medical, Dental, Vision

Life Insurance

Disability Insurance

401(k) plan

Employee stock purchase plan

11 Company holidays, PTO and leave

Job summary

TriNet is seeking a Staff MLOps Engineer to design, implement, and optimize machine learning operations within our infrastructure. You will work closely with data scientists, software engineers, and cross-functional teams to ensure robust deployment and maintenance of ML models.

You will develop scalable infrastructure, automate training and deployment pipelines, and manage monitoring, security and governance across production environments. This role offers hybrid work and Atlanta-based options.

Qualifications

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

Responsibilities

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

Skills

Python

Java

DevOps

MLOps

Education

Bachelor's Degree in Computer Science/Engineering

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

TriNet is seeking a Staff MLOps Engineer to design, implement, and optimize machine learning operations within our infrastructure. You will work closely with data scientists, software engineers, and cross-functional teams to ensure robust deployment and maintenance of ML models.

You will develop scalable infrastructure, automate training and deployment pipelines, and manage monitoring, security and governance across production environments. This role offers hybrid work and Atlanta-based options.