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Salary
$75k – $188k per year (gross)
Location
In office (Singapore)
Seniority
Senior · 5+ years exp
Employment
Full-Time

First seen by Alion on Sep 24, 2026.

Overview
Company
Impact
Profile match
A one-stop enterprise management solution. Kuailu AI unifies CRM, HR, finance, procurement, and meeting management on a single AI-powered platform. Eliminate data silos, gain real-time business insights, and accelerate digital transformation with AI Agents.

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.

Skills

Architectural Modeling, Deep Learning, Distributed Processing, Research Industry, Leadership, Foundation Design, Natural Language Processing, Optimisation Techniques, Model Training, Scientific Expertise, Driving, LLMs, GPU Programming, Lead Construction, PhD thesis, Research

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