Roles & Responsibilities

We are looking for a LLM Engineer/Researcher to continue to fine-tune and train our LLM models.

Responsibilities

• Train and Fine-tune foundational LLM models (e.g. PEFT, Lora, QLora, latest research techniques)
• Build and maintain LLM applications and infrastructure to meet business needs
• Design LLM inference infrastructure to scalably deploy LLMs within infrastructural constraints
• Research and utilise best of class tools within LLM ecosystem (e.g. Vector databases, LlamaIndex, etc)
• Keep up with latest research around LLMs (e.g. sparse models, hardware-specific LLMs)
• Research and keep up with latest use-cases of LLMs (e.g. RAG, Agents, etc)
• Collaborate closely with LLM research teams to participate in foundation model research, specifically for training productivity-related LLMs.

Requirements

• Experience with LLMs, including popular foundational models like Llama2 and MPT
• Experience with training and fine-tuning foundational LLM models
• Experience with quantisation techniques, including llama.cpp, GPTQ, etc
• Experience with LLM related development, e.g. Llamaindex, Langchain, Vector DBs, Prompt Engineering etc
• [Plus but not required] Experience running LLMs in production (e.g. Triton Inference Server, etc)

Tell employers what skills you have

Statistical Inference
Machine Learning
Usability
User Experience
Usability Testing
fine tuning
Inference engine
User Experience Design
User Research
UX
Databases

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