Data Scientist
Tasks
- Build retrieval pipelines with vector databases
- Design prompt engineering strategies and guardrails
- Develop and deploy LLM-based applications
- Ensure responsible AI practices
- Fine-tune and optimize LLMs
- Implement end-to-end machine learning pipelines
- Implement feedback loops for models
- Integrate models via APIs and microservices
- Monitor model performance and drift
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Amazon SageMaker | Apache Spark | Azure Machine Learning | CI/CD | Cloud platform | Data Drift | Data drift monitoring | Docker | Drift monitoring | Embeddings | Faiss | FastAPI | Flask | GitHub Actions | Google Cloud | Google Cloud Platform | Kubernetes | Language Models | Language Processing | Large Language Models | MLflow | Machine Learning | Microsoft Azure | Model Monitoring | Natural Language | Natural Language Processing | Pinecone | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | Transformers | Vector Databases | Weights and Biases
Education
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