Founding Machine Learning Engineer
Tasks
- Apply modern NLP techniques
- Apply transformer architectures
- Build embedding models and ranking systems
- Build retrieval pipelines
- Build systems for structured data extraction
- Design and train models for classification
- Design and train models for entity resolution
- Design and train models for information retrieval
- Evaluate and improve model performance with experimentation
- Integrate machine learning systems into production APIs
- Own end to end development of core machine learning systems
- Use large language models for extraction and classification
Perks/Benefits
Skills/Tech-stack
Classification | Contrastive Learning | Cross-lingual NLP | Distributed Training | Embedding Models | Entity Resolution | Experimentation | GPU clusters | Information Retrieval | Knowledge graphs | LLM Inference | Language Models | Language Processing | Large Language Models | Metrics | Natural Language | Natural Language Processing | Ontologies | PyTorch | Python | Ranking Systems | Record Linkage | Representation Learning | Retrieval Pipelines | Taxonomies | Transformers
Education
N/A
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