Research Scientist — AI & Large-Scale ML

Google Inc.; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google’s Mountain View-based Lab is seeking a Research Scientist to drive the Stitch research agenda, focusing on agentic AI and large-scale ML systems. You will lead decoding experiments, publish findings, and contribute to Gemini improvements, collaborating with universities and internal teams.

Responsibilities include designing novel architectures, building evaluation benchmarks, and advancing memory and planning for complex software tasks.

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 areas: agentic AI, RLHF, RLVF, RLGF, offline RL.
• One or more scientific publication submissions for conferences, journals, or public repositories.

Responsibilities

• 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 automated workflow optimization, multi-agent decomposition, and self-improvement.
• Explore techniques for scalable memory and context management that enable reasoning over large codebases.
• Lead research into synthetic data generation, verification methods/environments and rewards for Gemini improvement.
• Develop high-fidelity evaluation frameworks that measure agent impact to software quality and developer productivity.

Education

PhD in Computer Science or related field

Tools

JAX

PyTorch

Job description

Google’s Mountain View-based Lab is seeking a Research Scientist to drive the Stitch research agenda, focusing on agentic AI and large-scale ML systems. You will lead decoding experiments, publish findings, and contribute to Gemini improvements, collaborating with universities and internal teams.

Responsibilities include designing novel architectures, building evaluation benchmarks, and advancing memory and planning for complex software tasks.