Staff Software Engineer, AI/ML, Google Labs

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. Labs is a group focused on incubating early-stage efforts in support of Google’s mission to organize the world’s information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer timeframes. 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 . Design Minimum Viable Tests and prototypes to de-risk novel AI concepts. Execute technical spikes within short, iterative sprints to resolve architectural hurdles and prove core feasibility. Apply deep expertise in agentic systems—planning, memory, context, tool-use, and loops—to build novel design, coding, and product solutions. Blend Software Engineering with Product Management, Research, Data Science, UX Research functions and an entrepreneurial mindset. Analyze early technical and user signals to evaluate project feasibility and inform decisions. Prioritize rapid validation and learning; test for user and value, and technical feasibility to gather actionable signal before committing to scaled infrastructure. Grow in highly fluid, 0-to-1 environments. Partner closely within small, cross-functional teams to transform raw, ambiguous ideas into concrete technical and product directions. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience integrating generative AI tools or LLM interfaces into workflows. Preferred qualifications: Experience with AI/ML systems, particularly with Large Language Models (LLMs) and agentic systems. Experience with system design, evaluation methodologies, and quantitative data analysis. Understanding of agentic architectures, including loops, skills, context management, planning, tool use, evals. Ability to work in a small-team/startup, building new products and dealing with uncertainty and fluidity. Passion for developer tools, code AI, design AI, developer productivity, and improving software engineering workflows. Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience integrating generative AI tools or LLM interfaces into workflows.