Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 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).
• 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.)., and with Generative AI and Large Language Models (LLM).

Preferred qualifications:

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 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.

About the job
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.

In this role, you will be focused on integrating capabilities and experiences from both first-party Google Services and third-party services into Gemini, with the goal of making Gemini the best LLM-supercharged universal assistant available. You will be responsible for improving the tool use platform, enhancing horizontal model quality (in a joint effort with the OR team) for all services, skills, and agents that integrate with GeminiApp, and building new agentic experiences powered by these integrations.

Artificial intelligence will be one humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

The US base salary range for this full-time position is $207,000-$300,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Improve the model's ability to reason through complex agentic requests and chain multiple tools across multiple turns.
• Build new multimodal agentic experiences for Gemini Live, including camera and screen-sharing capabilities.
• Identify and bridge capability gaps for function calling based on user feedback.
• Develop scalable data collection and evaluation infrastructure, including autoraters, autousers, and automatic prompt optimization.
• Optimize Gemini's performance and frontiers through Model Context Protocol (MCP) integrations.

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Requisition #: 99181829663138502

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