Senior Software Engineer, GenAI Evaluation

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

• Design, build, and maintain reusable eval infra blocks, such as streaming evaluation, autorater pipelines, and metric aggregation.
• Make large-scale eval workflows more scalable, reliable, and efficient across compute, storage, and serving backends.
• Onboard product teams, debug their issues, and turn recurring needs into self-serve features.
• Build secure per-customer data isolation and access control for eval data and results.
• Help teams move smoothly from offline evals to online evals and to live experiments and production.

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with coding in Python.
• 3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
• 3 years of experience working with Generative AI agents.
• 2 years of experience with multithreading.

• Master's degree or PhD in Computer Science or a related technical field.
• 2 years of experience with large-scale data processing, storage systems, or workflow orchestration.
• 2 years of experience working with two or more of the following: distributed and parallel systems, machine learning, information retrieval, natural language processing, Unix/Linux environments, or security and access control.
• Experience with ML infrastructure, model evaluation, or LLM and GenAI workflows (e.g., autoraters, metrics, or experimentation platforms).
• Experience developing in Python and C++.