IBM Research is looking to advance efforts in building autonomous data management systems using foundation models and AI agents for tasks such as data discovery, knowledge representation, data access and retrieval with querying, and automated data-driven insights.
Requirements
- Pursuing graduate studies in computer science or related fields
- At least one main author research publication at a top conference in AI such as NeurIPS, AAAI, VLDB, SIGMOD, IJCAI, ICML, ICLR, and ICAPS
- Familiarity and working expertise with large language models
- Familiarity with knowledge graphs, SQL, RAG, Agentic frameworks
- Familiarity with reinforcement learning, AI planning
- Familiarity with prompt optimization techniques
Responsibilities
- [LLM for code generation] Using foundation models for code generation specific to data tasks such as SQL or NoSQL for data retrieval, python code generation for analytical insights.
- [Knowledge Graphs, Multi-Modal FMs] Combining foundation models, knowledge graphs, multi-modal structured and unstructured data to improve data discovery and automated Text-to-SQL.
- [FM Inference] Improving FM inference for both answer quality and computational cost.
- [LLMs for DataOps] Creating generative-AI tooling for DataOps (e.g., data integration and flows), analogous to DevOps accelerators but for data engineering and analytics.
- [Efficient and Reliable AI Agents] Creating efficient AI Agents that can reliably operate as part of an autonomous system.
Other
- Bachelor's Degree
- Master's Degree
- Dedication to our clients success, innovation that matters, and trust and personal responsibility in all our relationships
- Ability to learn and develop yourself and your career
- Ability to be courageous and experiment everyday
