About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

On-Device Machine Learning (ML), especially with the rise of Generative AI, is central to Google's product portfolio. Unique experiences on Pixel and Android are powered by on-device Machine Learning (e.g., Speech Recognition, Camera, and Assistant/Translation). As we embark on a future with Generative AI experiences personalized on your device, our team is building the core capabilities powering it. Google offers low-level ODML frameworks like TensorFlow Lite and MediaPipe to run machine learning on Android, iOS, Web, and other mobile/embedded devices. To continue growth and drive the next-generation of ML functionality, we're investing heavily in improving overall usability

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.

Responsibilities

• Ramp to our frameworks in the form of E2E integrations between popular Hugging Face/JAX/PyTorch libraries and AI Edge Torch, MP LLM Inference API, etc.
• Sample apps demonstrating best practices including hardware accelerations, quantization, debugging and optimizing performance and quality.
• Onboard SOTA models to provide excellent self-serve out-of-the-box experience for users.
• Scale partnerships with Android Apps and Google Cloud Customers and drive improvements in the overall stack based on real customer needs.
• Define and implement automated processes and infrastructure to test APIs and user-journeys across diverse platforms and advocate for product excellence.