The posting
In most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development.
- 3 years of experience designing, building, and operating large-scale Machine Learning infrastructure and distributed systems.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- Experience with software development in C++ or Python, with a strong background in systems programming.
- Experience in architecting scalable machine learning pipelines, from data set management to automated model training.
- Experience in performing deep-dive forensics on distributed systems to root-cause failures across multiple languages and frameworks.
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.
As a software engineer on the Health and Home Infrastructure team in Zurich, you will build and maintain the software infrastructure that powers products relied on by millions of people in their daily lives.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
Responsibilities
- Help us advance the state of the art in preventive health care by predicting health risks, such as high blood pressure and insulin resistance, based on a treasure trove of fitness and medical data.
- Bring machine learning research into our products by partnering with our research teams.
- Build machine learning infrastructure for large-scale model training and evaluation.
- Improve and maintain our infrastructure for smooth operation and minimal toil.
- Build data pipelines for creating large-scale machine learning datasets of highly sensitive fitness and medical data. Drive platform unification and simplicity.



