Staff Software Engineer, Cloud AI/ML Infrastructure
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a global organization involving cross-functional, or cross-business projects.
- Ability to solve ambiguous problems, and grow in a fluid environment where AI technologies are continuously advancing.
- Experience with distributed computing leveraging GPUs.
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 in Cloud ML Compute Services, you will focus on driving advancement in AI infrastructure. The team tackles key challenges by optimizing ML workload performance at every layer across the technical stack from networking and data storage to ML models. The team is dedicated to providing AI developers with excellent experience on Google's AI infrastructure, supporting them through every stage from initial previews and proofs-of-concept to onboarding and production.
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 team 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 performance profiling, debugging, and troubleshooting of AI/ML training and inference workloads.
- Develop tools and software for our AI/ML Infrastructure to deliver excellent developer experience.
- Partner with cross-functional, cross-regional teams to ensure our AI/ML infrastructure delivers exceptional value and drives success for our customers.
- Identify and resolve performance bottlenecks, ensuring our infrastructure operates effectively.
- Shape the future of our AI/ML infrastructure by identifying gaps in the existing products and recommending enhancements.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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