Software Engineering Manager, Cloud ML Compute Services (Mandarin, English)

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Ability to communicate in Mandarin and English fluently to partner with local clients and regional partners.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience collaborating with customers and field teams.
• Experience developing internal quality and repro testing to cover critical user journeys.
• Experience working in AI/ML and Infrastructure technologies.
• Ability to drive product improvement through bug fixes and feature enhancements.

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

• Recruit, provide mentorship and technical guidance to the team including road map and direction for team deliverables as well as efficient execution.
• Partner with customers to optimize the performance of their AI/ML models on Google Cloud infrastructure. Lead performance profiling, debugging, and troubleshooting of customer training and inference workloads.
• Collaborate with internal infrastructure, ML teams to improve Google Cloud's ability to support AI workloads.
• Develop and deliver training materials and demos to empower customers and internal teams.
• Contribute to the continuous improvement of our products by identifying and reporting bugs and suggesting enhancements. Proactively identify and address technical bottlenecks hindering customer success.