Omni模型算法实习生
Tasks
- Analyze experiment results
- Build multimodal representation experiments
- Clean multimodal datasets
- Conduct ablation studies
- Develop training scripts
- Diagnose training issues
- Integrate foundation models with robot perception
- Log training runs
- Measure inference latency and performance
- Organize patents and technical documents
- Perform preference alignment
- Produce technical research briefs
- Record and document benchmark results
- Reproduce multimodal model algorithms
- Research multimodal model advances
- Run model quantization and distillation experiments
- Run multimodal alignment and sequence modeling experiments
- Run pretraining and finetuning
- Test multimodal module integration
- Validate annotations
- Verify interaction scenario functions
- Write optimization comparison documents
Perks/Benefits
- N/A
Skills/Tech-stack
Ablation Study | Annotation Validation | Cross-modal alignment | Data Analysis | Data Annotation | Data Annotation Validation | Data Preprocessing | Dataset cleaning | Distributed Training | Experiment design | Finetuning | Inference Optimization | Knowledge Distillation | Language Model | Large Language Model | Log Analysis | Modal Alignment | Model Quantization | Multimodal Generation | Pretraining | PyTorch | Python | Sequence Modeling | Streaming | Training Log Analysis | Transformer | Vision Language Model | Vision-language
Education
Regions
Countries
States
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