LLM Algorithm Engineer
Tasks
- Build GPU cluster management system
- Build code assistance and code review systems
- Build multi agent collaborative assistant systems
- Create knowledge based private assistant systems
- Design LLM deployment solutions
- Develop API services for LLM applications
- Develop RAG prompt engineering strategies
- Develop enterprise internal toolchains
- Implement model fine tuning using LoRA
- Integrate speech recognition into customer service platforms
- Optimize KV cache storage strategies
- Optimize LLM inference performance
Perks/Benefits
- English courses
- Meal allowance
- Online learning access
- Onsite gym
- Onsite massages
- Paid time off
- Parental leave
- Sick leave
- Team-building activities
- Work from home
Skills/Tech-stack
API Development | Agent systems | Attention Mechanisms | Autogen | CUDA | Customer Service | Customer service platforms | Fine Tuning | KV cache | Knowledge graphs | Langchain | Language Models | Large Language Models | LoRA | Multi-Agent | Multi-Agent Systems | Multi-Modal | NLP | NVLink | NVSwitch | PEFT | PyTorch | QLoRA | RAG | Retrieval-Augmented Generation | SGLang | Service platforms | Speech Recognition | TensorFlow | TensorRT-LLM | Transformer | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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