Research Scientist - Large-Scale Machine Learning Systems (SysML) - Global Tech Research Program - 2027 Start (PhD)
Tasks
- Apply heterogeneous hardware for multimodal recommendations
- Build large-scale recommendation systems
- Design multimodal co training architectures
- Develop multimodal inference engine
- Develop multimodal representation fusion methods
- Develop multimodal training framework in PyTorch
- Improve training and inference efficiency
- Optimize long sequence end to end modeling
Perks/Benefits
- N/A
Skills/Tech-stack
Algorithm Engineering | Computer Vision | Federated Learning | Graph computing | High Performance | High-Performance Computing | Language Processing | Machine Learning | Memory Networks | Mixed Precision | Mixture of Experts | Multimodal Learning | Natural Language | Natural Language Processing | Performance Computing | PyTorch | Recommendation Systems | Representation Learning | Search and Recommendation | Sequence Modeling | Sparse MoE
Education
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