多模态大模型算法工程师
Tasks
- Analyze bad cases
- Automate data collection and labeling
- Build data model iteration loop
- Build multimodal data pipelines
- Design multimodal training data lifecycle management
- Drive SFT data engineering
- Fine tune and evaluate multimodal models
- Generate synthetic multimodal data
- Implement RLHF preference alignment data
- Lead pretraining data construction
- Optimize data throughput and loading
- Perform data cleaning de duplication filtering
- Reproduce state of the art scaling law research
- Run data ablation and attribution analysis
- Support distributed model training
Perks/Benefits
- N/A
Skills/Tech-stack
Agile | Attribution Analysis | Automatic Labeling | Computer Vision | Data Ablation | Data Augmentation | Data Deduplication | Data Engineering | Data Filtering | Data cleaning | Deep learning | Distributed Training | Fine Tuning | Git | Human Feedback | Instruction Fine-Tuning | Language Processing | Learning from Human Feedback | Model Fine-tuning | Multimodal Learning | Natural Language | Natural Language Processing | Pretraining | PyTorch | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Shell | Synthetic data
Education
N/A
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