<h1> </h1> <h2>About Eon</h2> <p>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.</p> <h2>The Role</h2> <p>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.</p> <p>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.</p> <h2>Research Areas</h2> <ul> <li> <p><strong>Query Processing and Query Engines:</strong> Query optimization and execution over columnar and lakehouse formats, including Apache Iceberg and Parquet, as well as approximate query processing using sketches and synopses.</p> </li> <li> <p><strong>Storage Systems:</strong> Deduplication, compression, and data layout optimization for large-scale storage.</p> </li> <li> <p><strong>Data Integration and Discovery:</strong> Entity resolution, schema matching, table joinability, and data discovery, including the use of LLMs as judges.</p> </li> <li> <p><strong>Information Retrieval and RAG:</strong> Retrieval-augmented generation over enterprise data, including emails, documents, and databases.</p> </li> <li> <p><strong>LLM Evaluation and Benchmarking:</strong> Evaluation frameworks and benchmarks for LLM agents working with enterprise data.</p> </li> <li> <p><strong>LLMs for Software Engineering:</strong> CI failure diagnosis, automated debugging, and program repair.</p> </li> </ul> <h2>Requirements</h2> <ul> <li> <p>PhD in Computer Science or a closely related field. The degree must be completed; candidates currently pursuing a PhD will not be considered.</p> </li> <li> <p>A deep, sustained research track record in at least one of the relevant areas listed above.</p> </li> <li> <p>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.</p> </li> <li> <p>At least 5 years of industry research experience, including work that has been deployed in production.</p> </li> <li> <p>Hands-on experience with LLMs, including prompting, fine-tuning techniques such as LoRA, model evaluation, and running batch inference on GPUs.</p> </li> <li> <p>Strong Python skills and the ability to independently design, implement, and execute end-to-end experiments.</p> </li> <li> <p>Excellent written English and the ability to communicate complex research findings clearly.</p> </li> </ul> <h2>Nice to Have</h2> <ul> <li> <p>Experience in storage, backup, data protection, or enterprise data management.</p> </li> <li> <p>Research or engineering experience with query engines, lakehouse formats, or approximate query processing.</p> </li> <li> <p>Experience with cloud platforms such as AWS, Azure, or GCP.</p> </li> <li> <p>Patents or a track record of translating research into intellectual property.</p> </li> <li> <p>Experience working with enterprise data sources, including Microsoft 365, email, documents, and databases.</p> </li> </ul> <h2>What You'll Do</h2> <ul> <li> <p>Lead applied research at the intersection of AI, data systems, information retrieval, and large-scale storage.</p> </li> <li> <p>Identify and investigate challenging technical problems related to making enterprise backup data more searchable, accessible, and useful for AI applications.</p> </li> <li> <p>Design, implement, and evaluate research ideas through hands-on experimentation, prototyping, and benchmarking.</p> </li> <li> <p>Develop novel approaches to query processing, data discovery, entity resolution, retrieval, and LLM-powered systems.</p> </li> <li> <p>Collaborate closely with Assaf Natanzon, VP and Chief Architect, and Eon's engineering and product teams to translate research findings into production-ready capabilities.</p> </li> <li> <p>Publish research in leading peer-reviewed conferences and contribute to patent applications.</p> </li> <li> <p>Build evaluation frameworks and benchmarks to measure the quality, accuracy, and performance of AI systems operating on enterprise data.</p> </li> <li> <p>Stay current with advances in AI and data systems, identify promising research directions, and turn them into practical innovations for Eon's platform</p> </li> </ul> <p> </p>