Staff Software Engineer, AI/LLM, Platforms and Devices

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience leading machine learning design and optimizing machine learning infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience testing, and launching software products.
• 3 years of experience with software design and architecture.
• Experience with Generative Modeling.
• Generative AI Agent Experience.

Preferred qualifications:

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience in software development, and with data structures/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.

We bridge the gap between cutting-edge AI/ML and real-world impact by embedding our expert Machine Learning engineers directly within Google's top Platforms and Devices product teams. This close partnership ensures that our advanced AI/ML solutions are seamlessly integrated into products that are used by billions of people every day!Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

The US base salary range for this full-time position is $197,000-$291,000 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

• Partner across Platforms and Devices product, research, and Google DeepMind to deliver cutting-edge, AI-driven product experiences.
• Guide the technical work of machine learning engineers on the team, providing mentorship and ensuring high standards of execution.
• Own the end-to-end machine learning life-cycle including design, development, training, evaluation, and hand-over the model to the Platforms and Devices product teams.
• Architect the shared machine learning models and infrastructure, identifying cross-project synergies to maximize impact.
• Collaborate closely with the bengaluru team to facilitate knowledge transfer and ensure effective project execution.