AI Engineer (PhD Required)
Tasks
- Build multimodal models for video image text and behavioral data
- Build tool integrated AI agents
- Create context aware retrieval for complex documents
- Develop advanced chunking and semantic retrieval
- Develop chain-of-thought and verification mechanisms
- Develop multi agent architectures for fraud detection
- Implement RAG architectures with vector databases and hybrid search
- Implement reasoning systems with compute optimization
- Optimize inference time compute allocation
- Research agent safety and alignment in production
- Research cross modal learning for fraud pattern detection
Perks/Benefits
- Annual team events
- Casual team environment
- Flexible hours
- Internet reimbursement
- Opportunity for advancement
- Remote work environment
Skills/Tech-stack
Attention Mechanisms | Autogen | Chunking | Constitutional AI | Distributed Training | GPU Optimization | Hugging Face | Hugging Face Transformers | Hybrid search | Knowledge Distillation | Langchain | Learning operations | Linear Algebra | MLOps | MLflow | Machine Learning | Machine Learning Operations | Mixture of Experts | Multimodal Learning | Optimization | PyTorch | Python | Quantization | Ray | Reinforcement Learning | Retrieval-Augmented Generation | Reward Modeling | Semantic Search | Statistics | TensorBoard | TensorFlow | Transformer Architectures | Vector Database | Weights and Biases
Education
Roles
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