Data Engineer II
Tasks
- Build scalable LLM pipelines
- Design large language model capabilities
- Develop LLM prototypes and proof of concepts
- Develop and operationalize fine tuning pipelines
- Develop prompt engineering strategies
- Ensure model governance security and performance
- Evaluate emerging LLM technologies
- Implement retrieval-augmented generation solutions
- Lead technical discussions and mentor team members
Perks/Benefits
Skills/Tech-stack
Amazon Web Services | CI/CD | Cloud platform | Deep learning | Distributed Computing | Efficient Fine Tuning | Embeddings | Fine Tuning | GPU Computing | Generative AI | Google Cloud | Google Cloud Platform | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | LoRA | MLOps | Machine Learning | Microsoft Azure | Model Compression | Model Distillation | Model Governance | Monitoring | PEFT | Parameter efficient fine-tuning | Prompt engineering | Python | Quantization | Retrieval-Augmented Generation | Transformers | Vector Databases | Web Services
Education
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