LLM Research Scientist
Tasks
- Apply prompt engineering and knowledge grounded inference
- Build RAG pipelines
- Collaborate with engineering teams to deploy LLM workflows
- Design domain specific enterprise LLM solutions
- Develop SFT and IFT training pipelines
- Document research results and technical designs
- Integrate structured and unstructured engineering knowledge
- Investigate state of the art LLM technologies
- Prototype and evaluate LLM architectures
- Transition prototypes to production systems
Perks/Benefits
- N/A
Skills/Tech-stack
Agents | Amazon Web Services | Anomaly Detection | Automated testing | CI/CD | Classification | Cloud Computing | Continuous Delivery | Continuous integration | Data Imputation | Domain Adaptation | Feature Selection | Fine Tuning | Huggingface | Instruction Fine-Tuning | Knowledge Injection | Langchain | Language Models | Large Language Models | Llamaindex | Microsoft Azure | Model Alignment | Multimodal Models | Prompt engineering | PyTorch | Python | Python Scripting | Regression Modeling | Resampling | Retrieval-Augmented Generation | SQL | Series analysis | Statistical modeling | Supervised Fine Tuning | Survival analysis | Time Series | Time Series Analysis | Tool use | Transformer | Version control | Web Services
Education
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