Research Scientist, Stitch

• Define and pursue a long-term applied research agenda to overcome fundamental limitations of LLMs in long-horizon reasoning, planning, and tool use for complex software engineering tasks.
• Design and implement novel agentic architectures, exploring frontiers such as automated workflow optimization, multi-agent decomposition, and self-improvement.
• Explore techniques for scalable memory and context management that enable reasoning over large codebases (dynamic, structurally-aware context and memory).
• Lead research into synthetic data generation, verification methods/environments and rewards for building data and capability flywheels for Gemini improvement.
• Develop high-fidelity evaluation frameworks that measure agent impact to software quality and developer productivity.

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.
  
• Experience with modern ML frameworks such as JAX or PyTorch.
• Experience in one or more of the following areas: agentic AI (planning, tool use, memory), reinforcement learning (RLHF, RLVF, RLGF, offline RL).
• One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

• 2 years of coding experience.
  
• 1 year of experience leading research efforts and influencing other researchers.
  
• Experience designing and implementing novel evaluation benchmarks for LLMs, generative code models or agentic systems.
• Experience with program analysis, program synthesis, automated program repair, formal methods, or designing developer tools.
• Experience building, training, and fine-tuning large language models.

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.
  
• Experience with modern ML frameworks such as JAX or PyTorch.
• Experience in one or more of the following areas: agentic AI (planning, tool use, memory), reinforcement learning (RLHF, RLVF, RLGF, offline RL).
• One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).