AI Engineer (PhD Required)
Tasks
- Build multimodal models for video image text and behavioral data
- Design and implement multi agent architectures for autonomous fraud detection
- Develop RAG architectures with vector databases and hybrid search
- Develop agent coordination systems and decision making tools
- Develop verification mechanisms for high stakes decisions
- Implement chunking and context aware retrieval
- Implement reasoning systems and test time compute optimization
- Optimize inference compute allocation for analytical tasks
- Research agent safety and alignment for production
- Research cross modal learning for fraud pattern detection
- Translate research algorithms into production ML systems
Perks/Benefits
Skills/Tech-stack
Architecture Search | Attention Mechanisms | Autogen | Automl | Computer Vision | Deep learning | Distributed Systems | Distributed Training | Embeddings | GPU Acceleration | GPU Optimization | Hugging Face | Hugging Face Transformers | Hybrid search | Knowledge Distillation | Langchain | Language Models | Large Language Models | MLOps | Machine Learning | Mixture of Experts | Multimodal Learning | Neural Architecture | Neural Architecture Search | PyTorch | Python | Quantization | Ray | Reinforcement Learning | Retrieval-Augmented Generation | Reward Modeling | TensorFlow | Test Time Computation | Transformers | Vector Databases
Education
Roles
AI | AI Engineer | Engineer
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