About this role
Lead the design, development, and deployment of machine learning models and LLM-based applications, including RAG pipelines, embedding strategies, vector search, and agentic workflows; own end-to-end AI/ML solutions and architect scalable MLOps and deployment strategies. Evaluate and monitor model and LLM performance, implement guardrails, and optimize systems for latency, cost, scalability, and reliability.
Skills for this role
PythonMachine LearningLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Agentic WorkflowsPrompt EngineeringEmbedding WorkflowsVector DatabasesVector Search ArchitecturesLangChainLlamaIndexModel Serving FrameworksFastAPIMLflowCI/CD PipelinesContainerizationCloud DeploymentMLOpsModel MonitoringDrift DetectionRetraining PipelinesModel Lifecycle ManagementProduction-grade Data PipelinesData ValidationData LineageReproducibilityModel Evaluation MethodologiesFine-tuning Foundation ModelsPerformance OptimizationCost Optimization