Character AI LLM Architect & Model Training Lead

Zebra Strategic Outsource Solution Ltd; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

Zebra Strategic Outsource Solution Ltd is hiring for a hands-on ML/LLM engineer to architect modular system prompts, build long-term memory, and own response management across English, Cantonese and Mandarin. You will select models, lead data pipelines, and train/open-weight LLMs while optimizing GPU deployments for cost and speed.

Candidates should have strong Python/PyTorch skills and exposure to Hugging Face tools.

Qualifications

• 4+ years in ML or software engineering with 1+ years shipping LLM products to real users.
• Deep, hands-on prompt engineering — system-prompt design, few-shot, structured output, tool calling, prompt testing.
• You have built memory or RAG systems in production.
• You have fine-tuned open-weight LLMs and built the dataset yourself.
• Strong Python and PyTorch; comfortable with Hugging Face, distributed training and cloud GPUs.
• Experimentation rigor — you can describe an eval or test that failed and what you changed.
• Startup mindset — you ship fast, own outcomes and work directly with the founders.
• English and Chinese required; Japanese is a strong plus.

Responsibilities

• Architect a modular system-prompt framework — character identity, voice and style guides, world rules and safety layers per character/context.
• Build long-term memory — summarization, retrieval (RAG / vector DB), user-profile extraction, recall at the right moment.
• Own response management — persona consistency, tone and length control, safety refusals in character.
• Select and orchestrate models — frontier APIs and open-weight bases based on quality, license, cost.
• Lead the training-data pipeline — sourcing, consent, cleaning, de-duplication, PII removal, labelling and versioning.
• Generate and curate synthetic dialogue data; write annotation guidelines and manage labelling vendors.
• Train our own models — continued pre-training, SFT, LoRA and preference tuning (DPO / RLHF).
• Distil, quantize and deploy on GPU inference stacks (e.g. vLLM, TensorRT-LLM); manage compute budget.
• Build evaluation across tracks — golden sets, LLM-as-judge, persona-drift and safety red-teaming.
• Ship in English, Cantonese and Mandarin.

Skills

ML engineering

Prompt engineering

Memory / RAG systems

Open-weight LLM fine-tuning

Python

PyTorch

Hugging Face

Distributed training

Cloud GPUs

Experimentation

Startup mindset

English and Chinese

Tools

Hugging Face

TensorRT-LLM

vLLM

distributed training

Job description

Zebra Strategic Outsource Solution Ltd is hiring for a hands-on ML/LLM engineer to architect modular system prompts, build long-term memory, and own response management across English, Cantonese and Mandarin. You will select models, lead data pipelines, and train/open-weight LLMs while optimizing GPU deployments for cost and speed.

Candidates should have strong Python/PyTorch skills and exposure to Hugging Face tools.