Senior Software Engineer, Multimodal Machine Learning, Glasses
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 3 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Preferred qualifications:
- Master's degree or PhD in computer science, mathematics, applied stats, machine learning or equivalent practical experience.
- 5 years of experience with data structures/algorithms.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience conducting applied research to enable new functionality and improve the quality and efficiency of large language and multimodal models.
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Our team is at the forefront of building the next generation of conversational AI. We are developing agentic AI solutions for smart glasses, utilizing Gemini Live and Astra to create a unique and trusted multimodal experience. This technology delivers instant, natural conversational intelligence directly to the users, allowing them to navigate their world more immersively than ever.
For decades, the computing revolution has reshaped our world driven by breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR team is at the forefront of the next major leap – the convergence of AI and XR. This is more than just new devices – it's about reimagining how we interact with the world around us. We're building a future where lightweight XR devices pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.
The US base salary range for this full-time position is $166,000-$244,000 + 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
- Design, develop, and deploy scalable and robust agentic AI solutions for high-value, real-world multimodal conversational AI use cases on smart glasses.
- Gain a deep understanding of the Gemini Live and Astra tech stack and infrastructure. Optimize agent architecture/orchestration to ensure efficient deployment and operation at scale, with a focus on inference cost optimization.
- Take ownership of AI quality for production systems. This includes defining technical metrics, implementing evaluation frameworks, analyzing loss patterns, and driving improvements through data collection and smart data generation and model enhancements.
- Implement, optimize, and advance state-of-the-art AI techniques, with a focus on multimodal multimodal conversational quality, multimodal tool use and multimodal goal-oriented reasoning.
- Drive progress through rapid experimentation, proposing and validating hypotheses, implementing and testing new ideas, and iterating quickly to find optimal solutions.
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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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