Sobre este puesto de Senior Research Scientist, AI & Data Systems en Eon
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