Senior Software Engineer, On-Device Machine Learning

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.

LiteRT is Google’s next generation on-device AI framework, succeeding TensorFlow Lite (TFLite). It is designed to maximize the performance, efficiency, and portability of ML models on a wide array of edge devices, from mobile phones to embedded systems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

• Write and test product or system development code.
  
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  
• Develop LiteRT, Google's on-device AI framework for 1P and 3P, enabling SOTA hardware acceleration and use cases on edge platforms
• Enable on-device deployment of key models, such as Gemini Nano and Gemma, across various accelerators (GPU / Pixel TPU / NPUs / CPU) on Android, Chrome, and more.
• Improve performance of on-device model inference via optimizations in the model conversion, on-device runtime and kernel implementation.

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 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.
  
• 3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
  
• 5 years of experience with data structures and algorithms.
• Experience with on-device ML SDKs/tooling (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).
  
• Knowledge of ML converters/compilers, and hardware-accelerated ML inference techniques and proficiency in ML frameworks (e.g., PyTorch, JAX, TensorFlow).
  
• Understanding of Generative AI model architectures and their optimization for on-device execution.