IBM Research is seeking a PhD-level summer intern to help design and advance the next generation of Hybrid Cloud AI platforms, focusing on highly scalable systems for machine learning (training and inference) that are both novel and impactful.
Requirements
- PhD student in Computer Science, Computer Engineering, or related discipline
- Research background in systems for generative AI (training or inference)
- Experience with distributed systems or microservices for data or ML workloads
- Familiarity with cloud-native platforms (Kubernetes, Docker, or hybrid cloud environments)
- Proficiency in at least one of the following languages: Python, C++, Go, Java, or Rust
- Knowledge of open-source large language model frameworks (e.g., Hugging Face, PyTorch, DeepSpeed)
- Familiarity with open source serving platforms like vllm, llm-d, and KServe
Responsibilities
- Working with full-time IBM researchers on highly scalable systems for machine learning (training and inference) that are both novel and impactful.
- Research builds on open-source platforms like llm-d, Kubernetes, Kserve, and explores optimizations across the entire stack from GPU networking, model scheduling serving, AI platform optimization including inference optimization, performance modeling, and Compound AI / Agentic systems.
- Work with an agile team of researchers and engineers developing practical innovations in scalable GenAI systems that can impact thousands of developers and applications worldwide.
Other
- PhD-level summer intern
- Bachelor's Degree
- Master's Degree
- No Travel
- Onsite
