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

Smartsheet; Bengaluru; On-site; INR 2,800,000 - 5,600,000; Full time

Job summary

Smartsheet is seeking an experienced AI/ML Ops professional to design, deploy, and maintain scalable AI platforms. You will implement production-grade pipelines, manage infrastructure with Docker/Kubernetes, and ensure secure, cost-efficient operations while collaborating with data scientists and software engineers in Bengaluru.

Role requires 7–12 years of experience, strong Python/SQL skills, and hands-on work with Databricks Lakehouse, MLflow, and vector Knowledge Graph stacks.

Qualifications

• 7–12 years of Experience in designing, developing and maintaining AI/ML Ops platforms/pipelines
• Model deployment: package and deploy AI/ML services to production with reproducibility and interpretability
• CI/CD pipeline development to accelerate model deployment
• Infrastructure management for training and serving using Docker, Kubernetes, or serverless platforms
• Monitoring and observability for model performance, data drift, and latency; Monte Carlo experience is a plus
• Automating retraining and data pipeline workflows to keep models accurate
• Deployment of foundation models, fine-tuning workflows, and RAG stacks (Vector DBs, Knowledge Graph)
• Resource optimization to minimize cloud costs with low-latency inference
• Collaboration with data scientists, engineers to bridge model development and production
• Version control and governance using MLflow
• Security and compliance with data governance policies
• Technology evaluation and innovation for data infrastructure
• Troubleshooting data-related issues to ensure data platform stability
• Other duties as assigned

Responsibilities

• Design, develop, and maintain AI/ML Ops pipelines and platforms
• Package and deploy AI/ML services to production with reproducibility
• Build automated CI/CD pipelines for model deployment
• Provision and optimize cloud infrastructure (Docker, Kubernetes, serverless)
• Implement post-deployment monitoring for model performance and latency
• Automate retraining and data workflow pipelines
• Manage foundation model deployments and RAG stacks (Vector DBs, Knowledge Graph)
• Optimize cloud costs while maintaining low-latency inference
• Collaborate with data scientists and software engineers to bridge development and production
• Ensure data and code versioning with MLflow
• Uphold security and data governance policies
• Explore new data tech to improve data infrastructure
• Diagnose and resolve data platform issues

Skills

AI/ML Ops

Databricks Lakehouse

MLflow

Kubernetes

Python

SQL

Cloud platforms

Tools

Docker

Terraform

Vector DBs

Knowledge Graph

AWS Bedrock

Job description

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.

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