Senior AI/ML Ops Engineer I(Hybrid Bangalore India)

Smartsheet
Bangalore, India
Hybrid

Who this role is best for

Candidates with experience in AI/ML Ops platforms and cloud infrastructure will find this hybrid role in Bangalore, India, that emphasizes collaboration across data and engineering teams.

Best fit for

  • Candidates with hands-on AI/ML Ops experience and a background in cloud infrastructure management
    — “Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines”
  • Individuals who have automated retraining and data workflows with a focus on scalability and efficiency
    — “Automate retraining and data pipeline workflows to ensure models stay accurate over time”
  • Professionals with a track record of deploying foundation models and RAG stacks using vector databases
    — “Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks”

Things to consider

  • This role requires being legally eligible to work in India on an ongoing basis
    — “Legally eligible to work in India on an ongoing basis”
  • The role demands a strong grasp of Databricks Lakehouse ecosystem and associated AI/ML tools
    — “In depth experience in AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem”

How to stand out

  • Highlight experience in deploying AI/ML services with reproducibility and interpretability
    — “Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable”
  • Showcase specific projects involving infrastructure optimization for training and serving
    — “Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms”
  • Demonstrate familiarity with AI/ML governance and version control tools like MLflow
    — “Manage versioning for data, code, and models using tools like MLflow”
  • Emphasize experience with monitoring and observability tools, particularly Monte Carlo
    — “Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable”
  • Demonstrate knowledge of AI/ML frameworks such as LangChain and LangGraph
    — “Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Designed and implemented AI/ML Ops platforms
  • Managed deployment of AI/ML services
Typical background
7-12 years of experience in AI/ML Ops

Skills & requirements

Required

Ai/ml OpsCi/cd Pipeline DevelopmentInfrastructure ManagementMonitoring & ObservabilityAutomationVersion Control & GovernanceSecurity & ComplianceTroubleshooting

Preferred

AWS BedrockMonte Carlo

Stack & domain

Ai/ml OpsDockerKubernetesServerless PlatformsMlflowLangchainLanggraphAWS BedrockAi/mlCloud Platforms

About the role

Original posting from Smartsheet via Greenhouse

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

Job Description/ Responsibilities:

7-12 Years of Experience in Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines

Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable

CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools

Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms

Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable

Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.

Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable

Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users

Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.

Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.

Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data

Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure

Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform

Perform other duties as assigned

Required Skills:

Enterprise SaaS software solutions with high availability and scalability

Solution handling large scale structured and unstructured data from varied data sources

Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security

In depth experience in AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem

AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph

Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration

Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable

Programming languages like Python and SQL

Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting

Solution Cost Optimisations and design to cost

Legally eligible to work in India on an ongoing basis

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. 

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

#LI-Remote

Source: Smartsheet careers (Greenhouse)

Similar roles