Research Scientist - Driven Agent Self-Evolution - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

What you'll do

• Develop agent frameworks that learn continuously from traces, feedback, and environmental signals.
• Build log analytics pipelines to extract quality signals and usage patterns for system and model improvement.
• Apply LLM post-training, reasoning, and planning techniques, and collaborate to deploy research at scale.

What they ask for

• Completing or recently completed a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related discipline.
• Strong theoretical and practical foundation in machine learning, deep learning, reinforcement learning, or optimization.
• Research experience in at least one area: LLM-based agents, planning and reasoning, multi-agent systems, continual/lifelong learning, or LLM post-training.
• Strong Python programming skills, proficiency with ML frameworks, and a publication record at top-tier venues.

Nice to have

• Publications related to agent learning and adaptation, or research experience in LLM reasoning and planning.
• Experience training or fine-tuning LLMs, building or evaluating LLM-based agents, or feedback-driven optimization.

Tools

Python, PyTorch, TensorFlow, JAX, RLHF, DPO, GRPO

AI focus

Research on self-evolving agents, continual learning from interaction, LLM post-training, reasoning and planning, and evaluation-governance loops.