Senior AL/ML Ops Engineer-II (Hybrid in Bangalore)
Smartsheet6 months ago
Responsibilities
- Design, develop, and oversee the strategy and architecture of scalable and reliable AI/ML Ops platforms and pipelines.
- Package and deploy reproducible and interpretable AI/ML services to production.
- Design and implement automated CI/CD pipelines for model deployment.
- Provision and optimize model-training and serving infrastructure using Docker, Kubernetes, or serverless platforms.
- Implement post-deployment monitoring for model performance, data drift, and latency; Monte Carlo experience is preferred.
- Automate model retraining and data pipeline workflows.
- Manage foundation model deployment, fine-tuning workflows, and RAG stacks involving vector databases and knowledge graphs; AWS Bedrock experience is preferred.
- Optimize GPU and CPU utilization to control cloud costs while maintaining low-latency inference.
- Collaborate with data scientists, data engineers, and software engineers to connect model development with production systems.
- Manage versioning for data, code, and models using tools such as MLflow.
- Implement data security measures, support data governance compliance, and protect sensitive data.
- Evaluate emerging data technologies and improve the organization’s data infrastructure.
- Diagnose and resolve complex data-related issues to maintain data platform stability and reliability.
- Perform other duties as assigned.
Requirements
- Experience with enterprise SaaS software solutions requiring high availability and scalability.
- Experience handling large-scale structured and unstructured data from varied sources.
- Experience building and maintaining scalable, reliable, efficient, and secure AI/ML Ops platforms.
- Experience influencing product engineering designs for data, AI, and analytics use cases.
- In-depth experience with system design, AI/ML frameworks, and large-scale data using the Databricks Lakehouse ecosystem.
- Experience with Databricks AI/ML Ops workflows, MLflow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, and Knowledge Graph.
- Knowledge of LangChain and LangGraph for AI/ML Ops pipeline integration.
- Hands-on experience with at least one major cloud provider: AWS, Azure, or GCP; AWS-hosted data platform experience is preferred.
- Proficiency in Python and SQL.
- Experience with Kubernetes, CI/CD, infrastructure-as-code tools, preferably Terraform, observability, monitoring, and alerting.
- Experience with solution cost optimization and design-to-cost practices.
- Legally eligible to work in India on an ongoing basis.
Benefits
- Hybrid work arrangement in Bangalore, India.
- Opportunity to work across multiple teams and disciplines with ownership and growth opportunities.
- Equal opportunity workplace with interview accommodations available upon request.
Tech Stack
Categories
About Smartsheet
Smartsheet is the Intelligent Work Management platform. By aligning people and technology so organizations can move faster and drive innovation, Smartsheet enables its millions of users to achieve more. Visit www.smartsheet.com to learn more. Backed by enterprise-grade security, Smartsheet is used by more than 85% of the companies in the Fortune 500 to implement, manage, and automate processes across a broad array of departments and use cases.