…Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions. Preferred…

…integrating next-generation AI (Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic workflows) into daily operations, modernizing legacy enterprise middleware, and driving data…

…Key development areas will include the Linux (Android) kernel, device drivers, embedded firmware, Android userspace daemons, performance analysis, and Linux power management. You will…

…Join our innovative team and shape the future of software development with AI-driven solutions. — Implement retrieval-augmented generation (RAG) pipelines, prompt engineering strategies…

…Working knowledge of generative artificial intelligence building blocks, including large language models, prompt design, retrieval augmented generation, context design, evaluation methods, and safety controls…

…embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. You will manage blockers to production…

…This work includes embeddings, shared feature layers, unified models, ranking systems, and behavioral understanding that support retrieval, ranking, ads, and personalized experiences across Pinterest…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…production GenAI features, and solve hard problems at the intersection of knowledge graphs, multi-agent orchestration, LLM-powered personalization, and retrieval-augmented generation - all…

…Build scalable systems that use large language models, retrieval-augmented generation, embeddings, semantic search, knowledge graphs and related AI techniques to support security scenarios…

…Hands-on experience with modern Generative AI platforms (AWS Bedrock, OpenAI, Anthropic, etc.). Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…agent tool discovery and invocation. - Hands-on experience with retrieval-augmented generation (RAG), vector databases, and knowledge base configuration for production AI systems. - AWS…

…deployment patterns including retrieval-augmented generation (RAG), fine-tuning decision frameworks, knowledge base configuration, vector database selection, and chunking/embedding strategies. Cross-Functional & Go…

…prompt engineering, Retrieval-Augmented Generation (RAG) strategies, and model fine-tuning. Latent Pattern Recognition: Apply advanced ML techniques (e.g., embedding-based clustering, representation…

…Later in the week, you're on-site running a workshop where a customer's ML team is building their first retrieval-augmented generation…

…generate, refactor, and review embedded C/C++ at scale. Ability to build and maintain AI-augmented developer workflows : prompt libraries, agent rules, retrieval-augmented…

…including Retrieval-Augmented Generation (RAG) pipelines, agentic AI systems, and LLM-powered workflows Architect AI systems with production-level concerns: scalability, cost management, latency…

…of LLM application architecture, vector databases, Retrieval-Augmented Generation (RAG), and evaluation frameworks. High proficiency in Python and SQL, with experience building functional applications…

…Service and Azure AI Foundry, including model deployment, capacity management, embeddings, and integration with Azure AI Search (Vector Search). RAG (Retrieval-Augmented Generation) Ability…

…containers and serverless architectures Experience with retrieval-augmented generation approaches, including embeddings and semantic search, and practical context engineering Proficiency building APIs and service…

…efficiency, and safe deployment in production environments. Leverage modern AI technologies such as large language models, embeddings, vector stores, and retrieval-augmented generation to…