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

What you'll do

• Research and develop multimodal moderation models, including MoE training, cross-modal alignment, and unified understanding and generation.
• Build agentic moderation systems using reinforcement learning, dynamic context, and tool collaboration for multi-step decision-making.
• Improve generalization and adversarial robustness across languages and content types.

What they ask for

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

Nice to have

• Practical implementation expertise in advanced LLM systems; familiarity with PEFT, RL, MoE, CoT, or Langchain.
• Research publications or LLM community contributions; experience in inference acceleration, AI system evaluation, or agent development.

Tools

Python, Rust, C++, pytorch, deepspeed, megatron, vllm, Langchain

AI focus

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