【27届校招】Omni模型算法工程师/研究员
Tasks
- Accelerate inference with low latency deployment
- Apply reinforcement learning for model training
- Build long context understanding models
- Build multimodal datasets construction and quality evaluation
- Conduct instruction tuning and preference alignment
- Deploy models on edge devices and heterogeneous platforms
- Develop multimodal understanding reasoning generation
- Implement cross modal alignment and fusion
- Integrate multimodal models with robot perception cognition decision control
- Optimize model compression quantization distillation
- Optimize real time streaming interaction
- Research multimodal model architectures
- Train multimodal models with data processing
Perks/Benefits
- N/A
Skills/Tech-stack
Context modeling | Data Engineering | Distributed Training | End to End | End to End Generation | Inference acceleration | Instruction Tuning | Knowledge Distillation | Language Model | Large Language Model | Long Context | Long Context Modeling | Model Compression | Multimodal | Preference alignment | PyTorch | Python | Quantization | Real Time | Real-time Streaming | Reinforcement Learning | Speech Recognition | Transformer | Vision Language Model | Vision-language
Education
Regions
Countries
States
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