Research Engineer in Large Model System
| Company | ByteDance |
|---|---|
| Location | San Jose, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Mid Level, Senior |
Requirements
- has research or technical backgrounds in LLM, code generation, large pre-trained models
- Candidates with pre-training foundation technologies, including efficient training and pretraining as a service
Responsibilities
- design and development of the architecture of large-scale machine learning systems, solving technical difficulties such as high concurrency, high reliability, and high scalability of the system.
- Covering various sub-directions of machine learning system, including resource scheduling, model training, model inference, data management, and workflow orchestration.
- Responsible for the research and introduction of advanced technologies in machine learning systems, such as the latest hardware architecture, heterogeneous computing systems, and compiler-based optimization technologies.
- Working closely with the algorithm teams to optimize the algorithm and system jointly.
Preferred Qualifications
- Candidates with top-tier conference papers, including NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, KDD, etc., relevant internship experience or winners of ACM competitions
- Proficient in deep learning frameworks such as PyTorch and TensorFlow, and programming languages such as Python or Java.