AI application engineer
Tasks
- Build AI agent systems
- Build RAG knowledge bases
- Build intelligent production scheduling systems
- Build intelligent quality inspection systems
- Build knowledge question answering systems
- Build predictive maintenance systems
- Centralize data and capabilities
- Collaborate on model optimization implementation
- Compress AI models
- Conduct rapid experimentation
- Deploy AI models
- Design AI application systems
- Develop AI capability platforms
- Ensure system scalability
- Ensure system stability
- Optimize AI model performance
- Optimize models for quantization
- Resolve model accuracy degradation
- Resolve performance bottlenecks
- Run proof-of-concept projects
- Summarize methodologies
- Write experiment reports
- Write technical documentation
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | Computer Vision | Django | Docker | Faiss | FastAPI | Flask | Language Models | Large Language Models | Linux | Linux deployment | Machine Learning | Milvus | Model Compression | Model Quantization | NumPy | Pandas | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Transformers | VLLM | Vector Databases | Weaviate
Education
Roles
AI | AI Application Engineer | Application Engineer | Engineer
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