Applied Scientist - Trust and Safety (Multimodal Foundation Model) - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

What you'll do

• Research and train multimodal moderation models, including MoE architectures, cross-modal reasoning, and unified understanding and generation.
• Develop agentic moderation systems using reinforcement learning, dynamic context assembly, and tool collaboration.
• Improve model generalization and robustness against multilingual content and adversarial AIGC.

What they ask for

• Completing or recently completed a PhD in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Strong understanding of cutting-edge LLM research.
• Proficiency in Python, Rust, or C++, and experience with deep learning frameworks.
• Strong understanding of distributed computing, performance tuning, and training, fine-tuning, or inference verification.

Nice to have

• Research project leadership and published papers or contributions to the LLM community.
• Experience with inference tuning and acceleration, AI accelerators, large-scale AI networks, AI evaluation, or agent development.

Tools

Python, Rust, C++, pytorch, deepspeed, megatron, vllm, GRPO/PPO

AI focus

Research and build multimodal safety foundation models and RL-driven agentic moderation systems, including synthetic data generation, tool collaboration, and adversarial robustness.