Senior Research Scientist, AI & Data Systems

About Eon Eon is building the next generation of cloud data protection, transforming cloud backups into accessible, searchable, AI-ready data assets. We combine advanced data systems, storage technologies, and AI to help enterprises unlock the value of their backed-up data. The Role As a Senior Research Scientist, AI & Data Systems at Eon Research, you will conduct applied research at the intersection of AI, data systems, and large-scale storage. Working closely with Assaf Natanzon, VP and Chief Architect, you will explore challenging technical problems, publish research in leading peer-reviewed venues, file patents, and translate research breakthroughs into production-ready product capabilities. This role is ideal for a researcher with a strong publication record, deep expertise in a relevant research area, and experience bringing research into real-world products. Research Areas - Query Processing and Query Engines: Query optimization and execution over columnar and lakehouse formats, including Apache Iceberg and Parquet, as well as approximate query processing using sketches and synopses. - Storage Systems: Deduplication, compression, and data layout optimization for large-scale storage. - Data Integration and Discovery: Entity resolution, schema matching, table joinability, and data discovery, including the use of LLMs as judges. - Information Retrieval and RAG: Retrieval-augmented generation over enterprise data, including emails, documents, and databases. - LLM Evaluation and Benchmarking: Evaluation frameworks and benchmarks for LLM agents working with enterprise data. - LLMs for Software Engineering: CI failure diagnosis, automated debugging, and program repair. Requirements - PhD in Computer Science or a closely related field. The degree must be completed; candidates currently pursuing a PhD will not be considered. - A deep, sustained research track record in at least one of the relevant areas listed above. - Publications in strong peer-reviewed conferences, such as VLDB, SIGMOD, ICDE, SIGIR, CIKM, FAST, OSDI, USENIX ATC, ACL, EMNLP, NeurIPS, ICML, ICLR, ICSE, or FSE, depending on the research area. - At least 5 years of industry research experience, including work that has been deployed in production. - Hands-on experience with LLMs, including prompting, fine-tuning techniques such as LoRA, model evaluation, and running batch inference on GPUs. - Strong Python skills and the ability to independently design, implement, and execute end-to-end experiments. - Excellent written English and the ability to communicate complex research findings clearly. Nice to Have - Experience in storage, backup, data protection, or enterprise data management. - Research or engineering experience with query engines, lakehouse formats, or approximate query processing. - Experience with cloud platforms such as AWS, Azure, or GCP. - Patents or a track record of translating research into intellectual property. - Experience working with enterprise data sources, including Microsoft 365, email, documents, and databases. What You'll Do - Lead applied research at the intersection of AI, data systems, information retrieval, and large-scale storage. - Identify and investigate challenging technical problems related to making enterprise backup data more searchable, accessible, and useful for AI applications. - Design, implement, and evaluate research ideas through hands-on experimentation, prototyping, and benchmarking. - Develop novel approaches to query processing, data discovery, entity resolution, retrieval, and LLM-powered systems. - Collaborate closely with Assaf Natanzon, VP and Chief Architect, and Eon's engineering and product teams to translate research findings into production-ready capabilities. - Publish research in leading peer-reviewed conferences and contribute to patent applications. - Build evaluation frameworks and benchmarks to measure the quality, accuracy, and performance of AI systems operating on enterprise data. - Stay current with advances in AI and data systems, identify promising research directions, and turn them into practical innovations for Eon's platform