Senior MLOps Engineer - Remote AI Infra Leader

Jobgether; United States; Presencial; USD 106.000 - 141.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Technical ownership

Learning opportunities

Inclusive culture

Travel occasionally

Descripción de la vacante

Jobgether is partnering with a government-focused organization to hire a Senior MLOps Engineer based in the United States. You will design and scale ML infrastructure, moving models from research to reliable production, and establish MLOps standards across teams.

You’ll own pipelines end-to-end, implement CI/CD for ML, monitor drift and data quality, and optimize costs for large-scale training and inference. This is a high-ownership role with substantial impact on AI capabilities at scale.

Formación

• 6–10+ years in software or ML engineering, with 3+ years in MLOps or ML infra.
• Strong Python and scripting skills; experience with Docker and Kubernetes.
• Experience deploying ML models to production and maintaining CI/CD pipelines.
• Familiarity with ML experiment tracking tools (MLflow, Weights & Biases) and Kubeflow.
• Knowledge of data versioning, model reproducibility, and production monitoring.
• Experience with Terraform or CloudFormation is beneficial.

Responsabilidades

• Design and maintain end-to-end ML pipelines for training, evaluation, deployment, and agentic AI workflows.
• Build infrastructure for training and serving across cloud platforms and GPUs.
• Develop tools for data pipelines, experiment tracking, and automated retraining.
• Collaborate with researchers and engineers to productionize PoCs as reliable systems.
• Implement CI/CD, automated testing, and deployment workflows for ML systems.
• Monitor models in production for performance, health, data quality, and drift.
• Improve infrastructure provisioning and data access with other teams.
• Optimize costs and performance for large-scale training and inference.
• Document standards and best practices for MLOps workflows.

Conocimientos

Python

Bash

Docker

Kubernetes

Cloud platforms

CI/CD pipelines

MLflow

Weights & Biases

Kubeflow

Model monitoring

Herramientas

Terraform

CloudFormation

Descripción del empleo

Jobgether is partnering with a government-focused organization to hire a Senior MLOps Engineer based in the United States. You will design and scale ML infrastructure, moving models from research to reliable production, and establish MLOps standards across teams.

You’ll own pipelines end-to-end, implement CI/CD for ML, monitor drift and data quality, and optimize costs for large-scale training and inference. This is a high-ownership role with substantial impact on AI capabilities at scale.