Senior Research Scientist, AI & Data Systems

• 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

• 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.

• 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.

• 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.

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.