Charm Security-Applied AI Researcher
Tasks
- Build retrieval pipelines
- Collaborate with infrastructure engineering teams
- Conduct applied research
- Conduct experiments in adversarial AI
- Develop AI driven fraud solutions
- Develop DAG orchestrated workflows
- Ensure regulatory compliance
- Evaluate performance alignment robustness
- Identify emerging fraud patterns
- Implement tool-use workflows
- Model behavioral patterns
- Prototype language model orchestration systems
- Scale and deploy models in production
- Track and experiment with LLM research
- Train and fine-tune large-scale models
Perks/Benefits
- N/A
Skills/Tech-stack
Adversarial AI | Agent systems | Agentic Reasoning | Airflow | Alignment | DAG Workflow Orchestration | DAG orchestration | Dagster | Deep learning | Fine Tuning | Hugging Face | LLM Fine-tuning | Langchain | Langgraph | Language Models | Large Language Models | Model Evaluation | Multi-Agent | Multi-Agent Systems | Neural Networks | Online Reinforcement Learning | Pinecone | Prefect | PyTorch | Python | Qdrant | RAG | RLHF | Reinforcement Learning | Retrieval-Augmented Generation | Tool use | Transformers | Vector Databases | Workflow Orchestration
Education
Roles
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