AI ML Ops Software Engineer (Bangalore Hybrid)

Smartsheet
Bengaluru
Workplace: RemoteFull timeFunction: Software EngineeringExperience: 4-6 yearsSkills: ["Collaboration","Troubleshooting","Problem-solving","Innovation","Cost optimization"]

Design, develop, and operate stable AI/ML Ops platforms and pipelines that package models for production and accelerate deployment through automated CI/CD. Provision and optimize infrastructure for training and serving using Docker, Kubernetes, or serverless, while implementing monitoring for performance, data drift, and latency. Automate retraining/data workflows, support foundation-model and RAG deployments, manage versioning with MLflow, and collaborate across data science and engineering to ensure scalability, security, and reliability.

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FursaFursa
Smartsheet
Smartsheet
1 day ago

AI ML Ops Software Engineer (Bangalore Hybrid)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 21 hours agoStatus: Live

Job Summary

Design, develop, and operate stable AI/ML Ops platforms and pipelines that package models for production and accelerate deployment through automated CI/CD. Provision and optimize infrastructure for training and serving using Docker, Kubernetes, or serverless, while implementing monitoring for performance, data drift, and latency. Automate retraining/data workflows, support foundation-model and RAG deployments, manage versioning with MLflow, and collaborate across data science and engineering to ensure scalability, security, and reliability.
Location: Bengaluru
Workplace: Remote
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Design, develop, and maintain reliable AI/ML Ops platforms and pipelines.
  • •Package and deploy AI/ML services to production ensuring reproducibility and interpretability.
  • •Build automated CI/CD pipelines for faster model deployment.
  • •Provision and optimize infrastructure for training and serving using Docker, Kubernetes, or serverless platforms.
  • •Implement post-deployment monitoring (model performance, data drift, latency) and automate retraining/data pipeline workflows.

Key Requirements

  • •4-6 years of experience in AI/ML Ops.
  • •Ability to package and deploy AI/ML services to production with reproducibility and interpretability.
  • •Experience designing CI/CD pipelines to accelerate model deployment.
  • •Hands-on infrastructure provisioning and optimization for training and serving using Docker, Kubernetes, or serverless platforms.
  • •In-depth experience with AI/ML Ops workflows and tooling in the Databricks Lakehouse ecosystem (including Databricks, MLflow, Unity Catalog, Vector Search, and Knowledge Graph).
Experience:4-6 yearsAI/ML OpsAI platformsEnterprise SaaSData engineering
Skills:CollaborationTroubleshootingProblem-solvingInnovationCost optimization
Tech Stack:DockerKubernetesAWSAzureGCPPythonSQLDatabricksMLflowMosaic AI Agent FrameworkUnity CatalogVector SearchKnowledge GraphLangChainLangGraphCI/CDTerraformObservabilityVector DBAWS Bedrock

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