AI Chief Scientist

UMELIFE (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 250,000 - 450,000; Full time

Job summary

UMELIFE (SINGAPORE) PTE. LTD. is seeking an AI Chief Scientist to lead our Foundation Model/LLM technology roadmap and model training strategy.

With NVIDIA GPU resources, you will drive pre-training, post-training, SFT, RLHF/RLAIF, and large-scale distributed training, and build an AI Research team from 0 to 1. This is a research-driven leadership role focused on advancing our Super AI Agent Platform.

Qualifications

• Strong hands-on experience in LLM training and foundation models.
• Deep expertise in pre-training, SFT, RLHF/RLAIF, and model optimization.
• Experience with large-scale GPU clusters and distributed training.
• Research background in AI/ML, DL, NLP or related fields.
• PhD or equivalent research experience preferred.

Responsibilities

• Lead Foundation Model / LLM architecture and technology roadmap.
• Drive pre-training, post-training, SFT, RLHF/RLAIF, and model optimisation.
• Lead large-scale distributed training and GPU infrastructure.
• Build and lead an AI Research team from 0 to 1.
• Integrate foundation model capabilities into our Super AI Agent Platform.

Skills

LLM training

Foundation Models

model architecture

distributed training

NVIDIA GPU clusters

AI/ML research

PhD or equivalent

Education

PhD or equivalent

Job description

We are building a proprietary LLM-powered Super AI Agent Platform and are seeking an AI Chief Scientist to lead our Foundation Model / LLM technology roadmap and model training strategy.

With NVIDIA B300 GPU resources already secured, we are committing dedicated compute and R&D resources to developing our own large-scale foundation model capabilities.

Key Responsibilities

• Lead Foundation Model / LLM architecture and technology roadmap
• Drive pre-training, post-training, SFT, RLHF/RLAIF, and model optimisation
• Lead large-scale distributed training and GPU infrastructure
• Build and lead an AI Research team from 0 to 1
• Integrate foundation model capabilities into our Super AI Agent Platform

Requirements

• Strong hands-on experience in LLM training, Foundation Models, model architecture, or distributed training
• Deep expertise in pre-training, SFT, RLHF/RLAIF, and LLM optimisation
• Experience with large-scale GPU clusters and distributed training
• Strong research background in AI/ML, Deep Learning, NLP, or related fields
• Experience from a leading AI lab, research institution, or top-tier technology company is highly preferred
• PhD or equivalent research experience preferred

This is a research-driven Foundation Model leadership role, not a traditional AI application or Agent product role.