Research Scientist Graduate (Multi-modal Agentic Databases) - 2027 Start (PhD)
ByteDance, Seattle, Washington
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The team
With the fast growth of Bytedance's business, Bytedance's system infrastructure is currently at a massive scale and requires versatile system solutions. With the large-scale deployment of large language models (LLMs) and AI Agents, traditional cloud-native infrastructure can no longer meet the extreme performance and elasticity demands of AI workloads. Our team works on advanced R&D projects in building multi-modal agentic database infrastructure, focusing on:
- Multi-modal query processing: Support seamlessly integrated multi-modal query processing, including vector, full-text and regular SQL query processing over various typed data. In addition, how to support large scale semantic operators in a cost-effective and low-latency way is also our research focus.
What you will do
- Do research surveys and come up with a new system and algorithm design.
- Develop new systems and successfully land them into production environments
- Be able to debug systems and measure system performance.
- Collaborate with mentors and other lab members.
- Write technical reports and publish papers.
What you need
- Individuals who are completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Skilled in at least one mainstream programming language (e.g., C/C++, Python, Go), with strong coding ability, data structures, and algorithm fundamentals.
- Be able to independently design and develop complex systems
- Deliver design documents, independent deliverables, and demo systems
- Be familiar with state-of-the-art data management technologies
Nice to have
- Strong learning ability and self-motivation. Good teamwork and communication skills.
- Excellent problem analysis and solving abilities.
- Capable of independently exploring solutions. Strong mental resilience and adaptability when facing challenges.
- Have research experience in LLMs and infrastructure is highly preferred
- Have published at least two papers as first authors in conferences or journals such as SIGMOD, VLDB, NSDI/OSDI, EuroSys etc.
Intelligence & Agent Architecture
- Explore infrastructure auto-optimization based on AI Agent workflows. Build a self-evolving business Agent framework, enabling full-stack intelligent optimization through “AI for Infrastructure”. We look into various ways to apply AI/LLM in solving infrastructure problems, such as NL-to-SQL, Auto Skills etc. This project aims to build next-generation AI-native infrastructure to support LLMs and AI Agents, improving resource utilization, reducing costs, enabling elastic scalability, and driving the evolution of AI infrastructure technologies.
To name a few, our TextToSQL project ranks top on well known industry benchmarks. We are also developing advanced technologies in supporting real-time semantic analysis in real production scenarios. Besides achieving great business impacts, we also encourage publishing on top tier conferences. In the past a few years, we have published dozens of papers in top tier conferences, such as SIGMOD, VLDB, ICLR, EuroSys etc. We hire students with great technical skills, willingness to learn and solve complex technical challenges and passion in making an impact on millions of users.
We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at ByteDance. Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume
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