Senior AL / MLOps Engineer

As we expand Smartsheet India, we're searching for Senior AI/ML Ops Engineers who crave variety and ownership. You'll have the opportunity to work across multiple teams and disciplines, building a versatile skill set while solving the complex challenges of a global platform.

Responsibilities:

• 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 and 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 and knowledge graphs). 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 and Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security and 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 organization'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.

Requirements:

• 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 the Databricks Lakehouse ecosystem.
• AI/MLOps workflows on Databricks, MLflow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, and Knowledge Graph.
• Knowledge of AI/ML frameworks like LangChain and 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 an 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 optimizations and design to cost.
• Legally eligible to work in India on an ongoing basis.