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The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company's AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. About the Scaling Research Team The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low‑level implementation details with engineering partners. 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Responsibilities - Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale. - Develop and optimize runtime inference services for large-scale AI applications. - Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world. - Conduct design and code reviews to ensure high standards of quality. - Create services, tools, and developer documentation to support the inference engine. - Implement robust and fault-tolerant systems for data ingestion and processing. 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