Lead Applied Scientist, Search - NLP/GenAI
CHF 128K-192K (estimate) Senior-level Full Time
Tasks
- Apply training methods balancing performance and latency
- Build document enrichment systems
- Construct knowledge graph pipelines with LLMs
- Design LLM based information extraction pipelines
- Design evaluation strategies for component and end to end quality
- Determine architectures balancing accuracy efficiency and scalability
- Develop annotation workflows and labeled datasets
- Develop evaluation frameworks for document understanding tasks
- Execute large scale semantic chunking projects
- Generate synthetic data for NLP training
- Lead end to end AI solutions for document understanding
- Lead knowledge distillation for production models
- Make technical decisions for chunking and knowledge extraction
- Mentor and coach ML NLP team members
- Optimize models for computational constraints
Perks/Benefits
- Career development
- Flexible vacation
- Headspace app
- Hybrid work model
- Mental health days
- Paid volunteer days off
- Retirement savings
- Tuition reimbursement
- Tuition reimbursement resources for wellbeing
- Work from anywhere up to 8 weeks per year
- Work-life balance flexibility
Skills/Tech-stack
Annotation Workflows | Citation Parsing | Data Generation | DeepSpeed | Document Classification | Document Understanding | Entity Linking | Entity recognition | Evaluation Frameworks | Few-Shot Learning | Few-shot | Hierarchical Taxonomy | Imbalanced Learning | Information Extraction | Knowledge Distillation | Knowledge graphs | Language Models | Language Processing | Large Language Models | Model Compression | Multi-label classification | Multi-task Learning | Natural Language | Natural Language Processing | PyTorch | Python | Query Answer Generation | Relation extraction | Semantic chunking | Synthetic Data Generation | Synthetic data | Transformers
Education
Roles
Applied Scientist | Lead | Lead Applied Scientist | Scientist
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