Senior Software Engineer, AI​/ML, Cloud

Senior Staff Software Engineer, AI/ML, Google Cloud

_corporate_fare_ Google _place_ Seattle, WA, USA;
Sunnyvale, CA, USA

** Advanced*
* Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

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Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
** Seattle, WA, USA;
Sunnyvale, CA, USA** .

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* Minimum qualifications:

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* + Bachelor's degree or equivalent practical experience.

+ 8 years of experience in software development.

+ 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

+ 5 years of experience with design and architecture; and testing/launching software products.

+ 5 years of experience with one or more of the following:
Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.

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* Preferred qualifications:

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* + Master's degree or PhD in Engineering, Computer Science, or a related technical field.

+ 8 years of experience with data structures/algorithms.

+ 5 years of experience in a technical leadership role leading project teams and setting technical direction.

+ 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

** 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $365000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google () .

** Responsibilities*
* + Design, develop, test, deploy, maintain, and enhance large scale software solutions.

+ Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.

+ Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.

+ Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.

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