AI Research Scientist, New Grad – Agents & Reinforcement Learning

The role

This person will design and develop agentic frameworks and build auto research and coding agents. They will conduct research in reinforcement learning and contribute to multi-agent systems within the Snowflake Data Cloud.

What you will do

• Design and develop agentic frameworks powered by recursive self-improvement loops
• Build and evaluate auto research agents
• Develop coding agents that understand, generate, and debug code
• Conduct research in reinforcement learning with a focus on RLHF, DPO, and PPO
• Contribute to multi-agent systems
• Develop and curate training data pipelines
• Publish research findings at top-tier venues such as NeurIPS, ICML, ICLR, and ACL

Required qualifications

• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field (completing or recently completed; or equivalent research experience)
• Foundational expertise in reinforcement learning algorithms, including RLHF, DPO, PPO, or multi-agent systems
• Research experience in LLM post-training, fine-tuning, or reasoning model development
• Demonstrated ability to implement and experiment with agentic architectures
• Proficiency in Python
• Strong mathematical and analytical foundation
• At least one first-author or co-authored publication or preprint in a relevant AI/ML area

Nice to have

• PyTorch or JAX
• Hands-on experience building or evaluating coding agents or auto research agents
• Familiarity with recursive self-improvement frameworks or automated AI scientist paradigms
• Experience with large-scale distributed training or efficient training paradigms
• Background in mathematical reasoning, structured decision-making, or program synthesis
• Exposure to domain-specific AI applications in healthcare, finance, or enterprise workflows

About the company

Snowflake is empowering enterprises to achieve their full potential. The company has a culture focused on impact, innovation, and collaboration.