AI Research Scientist

Responsibilities

• Design and develop agentic frameworks powered by recursive self-improvement loops
• Build and evaluate auto research agents capable of autonomous hypothesis formulation and experimentation
• Develop coding agents for complex, multi-step programming tasks
• Conduct research in reinforcement learning focusing on RLHF, DPO, and PPO
• Contribute to multi-agent systems involving collaboration and negotiation
• Develop and curate synthetic and human-annotated training data pipelines
• Publish research findings at top-tier venues such as NeurIPS, ICML, ICLR, and ACL

Requirements

• PhD in Computer Science, Machine Learning, AI, or a related field
• Foundational expertise in reinforcement learning (RLHF, DPO, PPO, or multi-agent systems)
• Research experience in LLM post-training, fine-tuning, or reasoning model development
• Ability to implement agentic architectures including tool-use and planning
• Proficiency in Python and deep learning frameworks like PyTorch or JAX
• Strong mathematical and analytical foundation
• At least one first-author or co-authored publication or preprint in AI/ML

Preferred Qualifications

• Experience building coding agents or auto research agents
• Familiarity with recursive self-improvement frameworks
• Experience with large-scale distributed training
• Background in mathematical reasoning or program synthesis

About the Company

Snowflake is empowering enterprises to achieve their full potential through the Snowflake Data Cloud. The AI Research team operates at the frontier of autonomous AI systems, building agentic infrastructure that ships into a platform used by thousands of enterprises.