Senior AI ML Operations Engineer

Smartsheet
Bengaluru
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Collaboration","Troubleshooting","Problem-solving","Cost optimization","Innovation"]

Design, develop, and maintain reliable AI/ML Ops platforms and pipelines, enabling reproducible model deployment to production. Build CI/CD for faster rollouts, provision and optimize infrastructure for training and inference, and implement monitoring for performance, drift, and latency. Automate retraining and data workflows, support foundation model and RAG deployments, and manage cost/compute efficiency. Govern versions with MLflow and ensure security, compliance, and stability through troubleshooting.

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FursaFursa
Smartsheet
Smartsheet
9 hours ago

Senior AI ML Operations Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 6 hours agoStatus: Live

Job Summary

Design, develop, and maintain reliable AI/ML Ops platforms and pipelines, enabling reproducible model deployment to production. Build CI/CD for faster rollouts, provision and optimize infrastructure for training and inference, and implement monitoring for performance, drift, and latency. Automate retraining and data workflows, support foundation model and RAG deployments, and manage cost/compute efficiency. Govern versions with MLflow and ensure security, compliance, and stability through troubleshooting.
Location: Bengaluru
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, develop, and maintain stable AI/ML Ops platforms and pipelines.
  • •Package, deploy, and govern AI/ML services for production to be reproducible and interpretable.
  • •Build automated CI/CD pipelines to accelerate model deployment.
  • •Provision and optimize infrastructure for training and serving using Docker, Kubernetes, or serverless.
  • •Implement monitoring for post-deployment model performance, data drift, and latency; automate retraining and data pipeline workflows.

Key Requirements

  • •Experience building and maintaining AI/ML Ops platform systems with scalability, reliability, efficiency, and security.
  • •Hands-on with AI/ML frameworks and tools for large-scale datasets using the Databricks Lakehouse ecosystem.
  • •AI/MLOps workflows on Databricks, MLflow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, and Knowledge Graph.
  • •Cloud experience with AWS, Azure, or GCP, with preference for AWS-hosted data platforms.
  • •Programming experience with Python and SQL, plus CI/CD and Kubernetes; Terraform (preferred).
Experience:Enterprise SaaSAI/ML OpsDatabricks LakehouseFoundation modelsRAGVector databasesLarge-scale structured and unstructured data
Skills:CollaborationTroubleshootingProblem-solvingCost optimizationInnovation
Languages:English
Tech Stack:DatabricksLakehouseMLflowMosaic AI Agent FrameworkUnity CatalogVector SearchKnowledge GraphLangChainLangGraphAWS BedrockVector DBsRAGDockerKubernetesServerlessAWSAzureGCPPythonSQL

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Smartsheet
Provides a cloud-based work management platform that enables teams to plan, track, automate, and report on work. Smartsheet combines spreadsheets, collaboration, and workflow automation to help organizations manage projects and processes at scale.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Bellevue, United States
Founded: 2005
WebsiteLinkedIn