大模型算法工程师（数据方向）
Tasks
- Analyze training loss and benchmarks
- Build data to model effect feedback loop
- Build quality modeling
- Deploy data algorithms in large scale processing pipelines
- Design pretraining data algorithms
- Diagnose data issues and iterate strategies
- Evaluate data source and filtering strategies
- Execute data ablation experiments
- Generate synthetic data
- Implement data filtering
- Perform deduplication
- Process training data with distributed frameworks
- Run course learning
- Select training data
- Tune data mixing
Perks/Benefits
- N/A
Skills/Tech-stack
Ablation Testing | Apache Spark | Benchmarking | Classifier Based Filtering | Cloud Computing | Data Analysis | Data Filtering | Data Processing | Data Quality | Data mixing | Data quality modeling | Deduplication | Deep learning | Distributed Computing | Embedding Based Filtering | JAX | Kubernetes | LSH | Language Processing | Loss analysis | Machine Learning | MinHash | Model Training | Natural Language | Natural Language Processing | Perplexity Filtering | PyTorch | Python | Quality modeling | Ray | SimHash | Synthetic data | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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