In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Partner with senior leads to architect closed-loop RSI pipelines that autonomously diagnose failure modes, refine instructions/trajectories, synthesize targeted training/eval data, and verify gains without manual intervention.
Investigate and build automated multi-agent systems that audit, compress, and de-conflict complex model context—maximizing token efficiency and inference speed while preserving behavioral and safety guardrails.
Bridge inference-time context engineering with model post-training (SFT/RL) to distill complex rules into model weights.
Advance automated optimization methods for production multimodal and reasoning systems.
Help define the multi-quarter roadmap across Engineering and Research teams, establishing rigorous automated evaluation gates.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience with ML design and with LLM/multimodal agent architectures.
Experience utilizing agentic AI frameworks or developer kits to build and deploy autonomous AI systems.
Experience in automated LLM evaluation (e.g., LLM-as-a-Judge, multi-turn user simulation, or Pareto optimization).
Experience integrating generative AI tools or LLM interfaces into workflows and designing metrics for the AI tools.
Preferred qualifications
8 years of experience with data structures and algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
Experience building Recursive Self-Improvement, automated prompt, or agent refinement frameworks (e.g., DSPy, OPRO, TextGrad, Reflexion, STaR).
Experience elevating performance on benchmarks for instruction-following, multimodal reasoning, and agents.
Experience with prompt compression, structured output enforcement, or context-to-weight distillation.
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience with ML design and with LLM/multimodal agent architectures.
Experience utilizing agentic AI frameworks or developer kits to build and deploy autonomous AI systems.
Experience in automated LLM evaluation (e.g., LLM-as-a-Judge, multi-turn user simulation, or Pareto optimization).
Experience integrating generative AI tools or LLM interfaces into workflows and designing metrics for the AI tools.
