
About this role
Full Time Senior Software Engineer III, Cloud AI/ML, Infrastructure in AI at Google in Taipei, Taiwan. Apply directly through the link below.
At a glance
- Work mode
- Office
- Employment
- Full Time
- Location
- Taipei, Taiwan
- Experience
- Senior · 2+ years
- Education
- PhD or equivalent
Core stack
- Natural Language Processing
- Artificial Intelligence
- Machine Learning
- Cross-functional
- Computer Science
- Infrastructure
- System Design
- Generative AI
- Google Cloud
- Optimization
- Performance
- Distributed
- Leadership
- Efficiency
- Debugging
- Profiling
- Security
- Python
- LLM
- ML
- UI
Quick answers
What are the qualifications?
Bachelor’s degree or equivalent practical experience.
What skills are required?
Natural Language Processing, Artificial Intelligence, Machine Learning, Cross-functional, Computer Science, Infrastructure, System Design, Generative AI, Google Cloud, Optimization, and more.
Google is hiring for this role. Visit career page
Taipei, Taiwan
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in Python or C++, or 1 year of experience with an advanced degree.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience with Generative AI, Large Language Models (LLM), or Machine Learning infrastructure, including model deployment, performance optimization, profiling, and debugging.
- Experience with distributed computing leveraging graphics processing units (GPU) or tensor processing units (TPUs).
- Ability to scope and solve problems independently, and thrive in a dynamic, fluid environment where AI technologies are continuously advancing.
- Ability to collaborate effectively with cross-functional and cross-regional teams.
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.The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
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.
Responsibilities
- Optimize performance on Google's AI infrastructure across the technical stack.
- Conduct in-depth performance profiling, debugging, and troubleshooting of AI/ML training and inference workloads.
- Develop tools and software for the AI/ML Infrastructure to deliver exceptional end-to-end developer experience.
- Partner closely with cross-functional, cross-regional teams to ensure the AI/ML infrastructure delivers exceptional value and drives success for the customers.
- Shape the future of the AI/ML infrastructure by identifying gaps in the existing products and recommending enhancements.