Senior AI/ML Ops Platform Engineer – Remote

Smartsheet; United States; À distance; USD 140 000 - 200 000; Plein temps

Résumé du poste

Smartsheet is seeking an experienced AI/ML Ops Engineer in the United States to design, deploy, and manage scalable AI/ML platforms. You will collaborate with data scientists and software engineers to bring models into production, ensure reproducibility, and optimize costs.

The role emphasizes Databricks Lakehouse, MLflow, and governance, with CI/CD pipelines, monitoring, and innovation in data tech to keep our data infrastructure cutting-edge.

Qualifications

• Experience designing and deploying AI/ML Ops platforms.
• Experience with Databricks Lakehouse ecosystem.
• Proficiency in Python and SQL; strong CI/CD practices.

Responsabilités

• Design, develop, and maintain AI/ML Ops platforms/pipelines.
• Package and deploy AI/ML services to production with reproducibility.
• Design automated CI/CD pipelines for model deployment.
• Provision and optimize infrastructure with Docker, Kubernetes, or serverless platforms.
• Implement post-deployment monitoring for model performance, data drift, and latency.
• Automate retraining and data pipeline workflows.
• Manage deployment of foundation models and RAG stacks (Vector DBs, Knowledge Graph).
• Optimize GPU/CPU usage to minimize cloud costs.
• Collaborate with data scientists, data engineers, and software engineers.
• Manage versioning for data, code, and models with MLflow.
• Ensure data security and governance; stay updated on data technologies.
• Troubleshoot data issues and perform other duties as assigned.

Connaissances

AI/ML Ops

Python

SQL

CI/CD practices

Problem solving

Outils

Databricks Lakehouse

MLflow

Mosaic AI Agent Framework

Unity Catalog

Vector Search

Knowledge Graph

Terraform

Kubernetes

AWS

GCP

Azure

Description du poste

Smartsheet is seeking an experienced AI/ML Ops Engineer in the United States to design, deploy, and manage scalable AI/ML platforms. You will collaborate with data scientists and software engineers to bring models into production, ensure reproducibility, and optimize costs.

The role emphasizes Databricks Lakehouse, MLflow, and governance, with CI/CD pipelines, monitoring, and innovation in data tech to keep our data infrastructure cutting-edge.