Applied Scientist, Search
Switzerland, Zug, Zug
R
CHF 126K-188K (estimate) Mid-level Full Time
Tasks
- Apply knowledge distillation to compress large models into efficient models
- Build document enrichment systems for taxonomy classification and metadata extraction
- Create LLM based knowledge graph construction pipelines
- Design build test and deploy AI document understanding solutions
- Design document understanding architectures for chunking classification and knowledge extraction
- Develop annotation workflows and evaluation frameworks for document understanding
- Develop semantic chunking models for legal documents
- Evaluate and optimize data and model performance with latency constraints
- Generate synthetic data for NLP model training and query simulation
Perks/Benefits
- Flexible vacation
- Headspace app access
- Hybrid work model
- Mental health days
- Retirement savings
- Tuition reimbursement
- Two Paid Volunteer Days Off
- Work from anywhere
- Work-life balance policies
Skills/Tech-stack
Data Annotation | Data Generation | Deep learning | DeepSpeed | Document Classification | Document Understanding | Hugging Face | Hugging Face Transformers | Information Extraction | Knowledge Distillation | Knowledge graphs | Language Models | Language Processing | Large Language Models | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | PyTorch | Python | Query Answering | Semantic chunking | Synthetic Data Generation | Synthetic data | Transformer Models
Education
Roles
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