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Remote and Bengaluru posting with known SaaS brand, but niche senior MLOps skills reduce competition.
Role requires specialized MLOps, Databricks, and vector/RAG experience, reducing industry transferability.
Many mandatory MLOps, Databricks, cloud, and deployment tooling requirements enforce strict filtering.
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Design, develop, and maintain AI/ML Ops platforms and pipelines ensuring scalability, reliability, and efficiency.
Package, deploy, and automate AI/ML models to production using CI/CD pipelines, infrastructure management (Docker, Kubernetes, serverless), and monitoring tools.
Manage resource optimization (GPU/CPU) and collaborate with cross-functional teams to bridge model development and production, including governance and security compliance.
Experience in building and maintaining AI/ML Ops platforms with scalable, reliable, and secure enterprise SaaS solutions handling large-scale structured and unstructured data.
Hands-on experience with at least one major cloud provider (AWS preferred), Kubernetes, CI/CD, IAC tools (preferably Terraform), Python, and SQL.
Experience with AI/ML frameworks and tools such as Databricks Lakehouse ecosystem, MLFlow, Unity Catalog, LangChain, LangGraph.
Legally eligible to work in India on an ongoing basis. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in deploying and managing complex AI/ML infrastructure on cloud environments, particularly AWS hosted platforms.
Proficient in handling AI/MLOps workflows involving large data volumes (Petabytes) using Databricks and related tools.
Comfortable leading automation, monitoring, cost optimization efforts, and ensuring compliance in AI/ML model deployment pipelines.