Data Science Lead
Tasks
- Build RAG architectures and retrieval strategies
- Collaborate with ML and backend engineers to productionize AI components
- Design and optimize LLM powered retrieval and validation pipelines
- Drive technical decisions for embeddings and vector databases
- Ensure reproducible testable and maintainable AI workflows
- Establish model evaluation benchmarking and continuous improvement
- Implement explainability traceability and validation mechanisms
- Improve system reliability model performance scalability and operations
- Lead AI and machine learning architecture for compliance validation
- Scale AI capabilities into enterprise platform
Perks/Benefits
Skills/Tech-stack
Benchmarking | Embeddings | Evaluation | Explainable AI | GenAI | Information Retrieval | Language Models | Large Language Models | Machine Learning | Model Validation | NLP | Python | RAG | Retrieval-Augmented Generation | Vector Databases
Education
N/A
Roles
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