Software Engineer, Generative AI

Google place Sunnyvale, CA, USA

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• 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 leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with GenAI techniques (e.g., Large Language Models, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

• 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 working in a complex, matrixed organization involving cross‑functional, or cross‑business projects.
• 3 years of experience in a technical leadership role; separately envisioning, bootstrapping and driving projects, setting roadmap and leading adjacent engineers with a track record of deliveries.
• Experience shipping products powered by AI/ML.
• Experience with the open‑source local large language model stack and ecosystem.

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.

On‑device Machine Learning (ODML) is central to Google’s product portfolio. The most unique experiences on Pixel, and Android today are already powered by on‑device Machine Learning – Speech Recognition, Camera, and Assistant/Translation.

Google offers low‑level ODML frameworks like Tensor Flow Lite and Media Pipe to run machine learning on Android, iOS, Web, and other mobile/embedded devices. It is now deployed across 4 billion+ devices, in 25 000+ Android apps, powering marquee features in Android, Search, Photos, Assistant, You Tube, and more. To continue growth and drive the next‑generation of ML functionality, we are investing in improving overall usability, on‑device performance, and the developer experience across all platforms.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise‑grade solutions that leverage Google’s cutting‑edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Individual pay is determined by factors including job‑related skills, experience, and relevant education or training.

US: $207 000 – $301 000 (USD) + 20% bonus target + bonus + equity + benefits

• Help bootstrap a brand new effort to bring the performance of LiteRT‑LM to agentic systems.
• Understand where the open‑source third‑party ecosystem is going and influence the direction of LiteRT‑LM to enable the most developer friendly integrations with popular agentic systems.
• Understand the needs of first‑party teams and build common infrastructure to enable the ability to use local Large Language Models (LLMs) from first‑party products.
• Develop the necessary infrastructure from local API…