Foundation Model Pre-training 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 training strategy. This role focuses on building cutting-edge large-scale AI capabilities for our proprietary Super AI Agent Platform.

You will oversee pre-training, fine-tuning, RLHF/RLAIF, and distributed training, while growing an AI research team from 0 to 1, and guiding architecture decisions across the stack. A PhD or equivalent research background is highly valued.

Qualifications

• 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.

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

GPU infrastructure

AI research

Education

PhD or equivalent

Tools

NVIDIA GPUs

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.