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