About The Position

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 manage information at a 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.

Requirements

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in Python.
  • Experience building and deploying Generative AI Agents that leverage Large Language Models (LLMs).
  • Experience in AI platform development, AI infrastructure, or applied Artificial Intelligence.

Nice To Haves

  • Master's degree or PhD in Computer Science or related technical field.
  • Experience with Machine Learning (ML) algorithms and tools (e.g., TensorFlow, PyTorch).
  • Experience in NLP, NLU, Machine Learning, LLMs, or in a related field.

Responsibilities

  • Design and launch critical, differentiating capabilities for continuous AI, such as a proactivity, personalization, context awareness, self-improvement, verification.
  • Strengthen multi-agent interaction and agent architectures, including planning, orchestration, continuous iteration and memory.
  • Enhance agent state management through context engineering, dynamic/content-aware updates and multiple knowledge sources.
  • Lead efforts to measure and hillclimb performance on custom benchmarks and industry-standard benchmarks (where applicable).
  • Own quality and reliability of agents in production related to performance, compliance and consistency.
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