AI Algorithm and Development Software Engineer
Tasks
- Build LLM evaluation system
- Conduct prompt engineering research
- Create multi agent collaboration mechanisms
- Design scalable agent system architecture
- Develop agent runtime system
- Fine-tune large language models
- Implement agent memory module
- Implement model reasoning technologies
- Integrate open source agent frameworks
- Optimize agent scheduling logic
- Optimize function calling for tools
- Participate in agile planning estimation retros on call
- Track LLM research trends
- Translate research into technical solutions
Perks/Benefits
Skills/Tech-stack
Agent architecture | Agent systems | AutoGPT | CUDA | Chain-of-Thought | Deep learning | Efficient Fine Tuning | Fine Tuning | Function Calling | Git | High Availability | Human Feedback | Langchain | Language Processing | Learning from Human Feedback | LoRA | Long Context | Machine Learning | Memory Module | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | OpenCWA | OpenMP | PEFT | Parameter efficient fine-tuning | Prompt engineering | PyTorch | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | SIMD | Scalability | Scheduling | State Machine | Supervised Fine Tuning | TensorFlow | Tool Call Framework | Tool invocation
Education
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