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Senior Software Engineer, ChromeOS, On-Device Machine Learning
Job Description
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., Python, C, C++).
- 5 years of experience testing, and launching software products.
- 3 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 3 years of experience in performance analysis and optimization including GPU programming, mobile GPU, system architecture, performance modeling, benchmarking, machine learning infrastructure, or other similar experience.
Preferred qualifications:
- Experience with ML frameworks (e.g., PyTorch, JAX, TensorFlow).
- Experience leading and delivering ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).
- Experience with on-device ML SDKs/tooling (e.g., TensorFlow Lite).
- Knowledge of ML converters/compilers and run-times, and hardware-accelerated ML inference techniques.
- Understanding of Generative AI model architectures and their optimization for on-device execution.
- Passion for innovation and for driving progress in on-device ML.
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.
Our team focuses on model quality, outputs, compilation to achieve a wide range of capabilities on device, and work with other teams in the Laptops & Tablets On-Device Machine Learning (L&T ODML) to build APIs for building engaging user experiences on device.
In this role you will be responsible for learning the foundations of ML modeling, neural networks, transformers, Generative Artificial Intelligence (genAI), optimization techniques like quantization, model compilation and op fusing, fine-tuning techniques like prompt tuning, and how they tie into the inference software stack to run across the entire laptop and tablet fleet of Android devices.
Responsibilities
- Bringup ML and GenAI models onto various compute (CPU, GPU and NPUs) across suite of devices (laptops and tablets).
- Test and benchmark model performance and quality across varying sizes and constraints.
- Work on fine-tune training and model quality optimizations along with model compilation and training.
- Build inference graphs that can leverage on-device models.
- Collaborate with power and performance teams to optimize model power/compute usage and memory footprint.
About us
Google’s mission is to organize the world‘s information and make it universally accessible and useful.
Since our founding in 1998, Google has grown by leaps and bounds. From offering search in a single language we now offer dozens of products and services—including various forms of advertising and web applications for all kinds of tasks—in scores of languages. And starting from two computer science students in a university dorm room, we now have thousands of employees and offices around the world. A lot has changed since the first Google search engine appeared. But some things haven’t changed: our dedication to our users and our belief in the possibilities of the Internet itself.