Foundation Model Pre-training Scientist

KUAILU SOFTWARE (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

KUAILU SOFTWARE (SINGAPORE) PTE. LTD. is seeking a Foundation Model Pre-training Scientist to lead our model roadmap and training strategy for a proprietary Super AI Agent Platform. The role reports on the architecture, training regimes, and optimization of foundation models at scale.

You will helm distributed training across GPU clusters, build an AI Research team from 0 to 1, and drive integration of foundation model capabilities into our platform, shaping the next generation of AI agents.

Qualifications

• Strong hands-on experience in LLM training and Foundation Models.
• 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.
• 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

Distributed training

NLP expertise

Education

PhD or equivalent

Job description

We are building a proprietary LLM-powered Super AI Agent Platform and are seeking an Foundation Model Pre-training 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.